diff --git a/docs/_posts/Cabir40/2024-10-21-bge_medembed_base_v0_1_en.md b/docs/_posts/Cabir40/2024-10-21-bge_medembed_base_v0_1_en.md new file mode 100644 index 00000000000000..f21ba93b82dd9c --- /dev/null +++ b/docs/_posts/Cabir40/2024-10-21-bge_medembed_base_v0_1_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English bge_medembed_base_v0_1 BGEEmbeddings from abhinand +author: John Snow Labs +name: bge_medembed_base_v0_1 +date: 2024-10-21 +tags: [embedding, en, open_source, bge, medical, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. +`bge_medembed_base_v0_1` is a English model originally trained by abhinand + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_medembed_base_v0_1_en_5.5.0_3.0_1729515433167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_medembed_base_v0_1_en_5.5.0_3.0_1729515433167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_medembed_base_v0_1","en")\ + .setInputCols(["document"])\ + .setOutputCol("embeddings") + +pipeline = Pipeline( + stages = [ + document_assembler, + embeddings +]) + +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = BGEEmbeddings.pretrained("bge_medembed_base_v0_1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val data = Seq("I love spark-nlp").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + +``` +
+ +## Results + +```bash + ++----------------------------------------------------------------------------------------------------+ +| bge_embedding| ++----------------------------------------------------------------------------------------------------+ +|[{sentence_embeddings, 0, 15, I love spark-nlp, {sentence -> 0}, [-0.018065551, -0.032784615, 0.0...| ++----------------------------------------------------------------------------------------------------+ + +``` + +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_medembed_base_v0_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|389.7 MB| \ No newline at end of file diff --git a/docs/_posts/Cabir40/2024-10-21-bge_medembed_large_v0_1_en.md b/docs/_posts/Cabir40/2024-10-21-bge_medembed_large_v0_1_en.md new file mode 100644 index 00000000000000..ef752830de8a8f --- /dev/null +++ b/docs/_posts/Cabir40/2024-10-21-bge_medembed_large_v0_1_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English bge_medembed_large_v0_1 BGEEmbeddings from abhinand +author: John Snow Labs +name: bge_medembed_large_v0_1 +date: 2024-10-21 +tags: [embedding, en, open_source, bge, medical, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. +`bge_medembed_large_v0_1` is a English model originally trained by abhinand + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_medembed_large_v0_1_en_5.5.0_3.0_1729515260623.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_medembed_large_v0_1_en_5.5.0_3.0_1729515260623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_medembed_large_v0_1","en")\ + .setInputCols(["document"])\ + .setOutputCol("embeddings") + +pipeline = Pipeline( + stages = [ + document_assembler, + embeddings +]) + +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = BGEEmbeddings.pretrained("bge_medembed_large_v0_1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val data = Seq("I love spark-nlp").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + +``` +
+ +## Results + +```bash + ++----------------------------------------------------------------------------------------------------+ +| bge_embedding| ++----------------------------------------------------------------------------------------------------+ +|[{sentence_embeddings, 0, 15, I love spark-nlp, {sentence -> 0}, [-0.018065551, -0.032784615, 0.0...| ++----------------------------------------------------------------------------------------------------+ + +``` + +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_medembed_large_v0_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| \ No newline at end of file diff --git a/docs/_posts/Cabir40/2024-10-21-bge_medembed_small_v0_1_en.md b/docs/_posts/Cabir40/2024-10-21-bge_medembed_small_v0_1_en.md new file mode 100644 index 00000000000000..b46280a80ba64c --- /dev/null +++ b/docs/_posts/Cabir40/2024-10-21-bge_medembed_small_v0_1_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English bge_medembed_small_v0_1 BGEEmbeddings from abhinand +author: John Snow Labs +name: bge_medembed_small_v0_1 +date: 2024-10-21 +tags: [embedding, en, open_source, bge, medical, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. +`bge_medembed_small_v0_1` is a English model originally trained by abhinand + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_medembed_small_v0_1_en_5.5.0_3.0_1729513920928.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_medembed_small_v0_1_en_5.5.0_3.0_1729513920928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +embeddings = BGEEmbeddings.pretrained("bge_medembed_small_v0_1","en")\ + .setInputCols(["document"])\ + .setOutputCol("embeddings") + +pipeline = Pipeline( + stages = [ + document_assembler, + embeddings +]) + +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = BGEEmbeddings.pretrained("bge_medembed_small_v0_1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val data = Seq("I love spark-nlp").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + +``` +
+ +## Results + +```bash + ++----------------------------------------------------------------------------------------------------+ +| bge_embedding| ++----------------------------------------------------------------------------------------------------+ +|[{sentence_embeddings, 0, 15, I love spark-nlp, {sentence -> 0}, [-0.07673764, -0.04207312, 0.026...| ++----------------------------------------------------------------------------------------------------+ + +``` + +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_medembed_small_v0_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|116.4 MB| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-09-dummy_model_jbao8899_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_jbao8899_pipeline_en.md new file mode 100644 index 00000000000000..d5ec2e1b7f6a1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-09-dummy_model_jbao8899_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_jbao8899_pipeline pipeline CamemBertEmbeddings from jbao8899 +author: John Snow Labs +name: dummy_model_jbao8899_pipeline +date: 2024-09-09 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_jbao8899_pipeline` is a English model originally trained by jbao8899. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_jbao8899_pipeline_en_5.5.0_3.0_1725852224773.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_jbao8899_pipeline_en_5.5.0_3.0_1725852224773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_jbao8899_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_jbao8899_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_jbao8899_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/jbao8899/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-10-burmese_awesome_qa_model_jleung1618_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-10-burmese_awesome_qa_model_jleung1618_pipeline_en.md new file mode 100644 index 00000000000000..84c78652b8e3ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-10-burmese_awesome_qa_model_jleung1618_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English burmese_awesome_qa_model_jleung1618_pipeline pipeline DistilBertForQuestionAnswering from JLeung1618 +author: John Snow Labs +name: burmese_awesome_qa_model_jleung1618_pipeline +date: 2024-09-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_jleung1618_pipeline` is a English model originally trained by JLeung1618. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jleung1618_pipeline_en_5.5.0_3.0_1725960567292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_jleung1618_pipeline_en_5.5.0_3.0_1725960567292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_qa_model_jleung1618_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_jleung1618_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_qa_model_jleung1618_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/JLeung1618/my_awesome_qa_model + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-11-babyberta_childes_2_5_0_1_finetuned_squad1_en.md b/docs/_posts/ahmedlone127/2024-09-11-babyberta_childes_2_5_0_1_finetuned_squad1_en.md new file mode 100644 index 00000000000000..d50566edbd0941 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-11-babyberta_childes_2_5_0_1_finetuned_squad1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English babyberta_childes_2_5_0_1_finetuned_squad1 RoBertaForQuestionAnswering from lielbin +author: John Snow Labs +name: babyberta_childes_2_5_0_1_finetuned_squad1 +date: 2024-09-11 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`babyberta_childes_2_5_0_1_finetuned_squad1` is a English model originally trained by lielbin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/babyberta_childes_2_5_0_1_finetuned_squad1_en_5.5.0_3.0_1726062103211.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/babyberta_childes_2_5_0_1_finetuned_squad1_en_5.5.0_3.0_1726062103211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_childes_2_5_0_1_finetuned_squad1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("babyberta_childes_2_5_0_1_finetuned_squad1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|babyberta_childes_2_5_0_1_finetuned_squad1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|32.0 MB| + +## References + +https://huggingface.co/lielbin/babyberta-CHILDES_2.5-0.1-finetuned-SQuAD1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-11-roberta_teste_en.md b/docs/_posts/ahmedlone127/2024-09-11-roberta_teste_en.md new file mode 100644 index 00000000000000..436ff060b74524 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-11-roberta_teste_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_teste RoBertaForQuestionAnswering from oGabrielFreitas +author: John Snow Labs +name: roberta_teste +date: 2024-09-11 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_teste` is a English model originally trained by oGabrielFreitas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_teste_en_5.5.0_3.0_1726036404321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_teste_en_5.5.0_3.0_1726036404321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_teste","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_teste", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_teste| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/oGabrielFreitas/roberta-teste \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-12-classifier_bias_sango_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-12-classifier_bias_sango_pipeline_en.md new file mode 100644 index 00000000000000..b620aac212599f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-12-classifier_bias_sango_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English classifier_bias_sango_pipeline pipeline DistilBertForSequenceClassification from Social-Media-Fairness +author: John Snow Labs +name: classifier_bias_sango_pipeline +date: 2024-09-12 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classifier_bias_sango_pipeline` is a English model originally trained by Social-Media-Fairness. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classifier_bias_sango_pipeline_en_5.5.0_3.0_1726124947223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classifier_bias_sango_pipeline_en_5.5.0_3.0_1726124947223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("classifier_bias_sango_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("classifier_bias_sango_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classifier_bias_sango_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Social-Media-Fairness/Classifier-Bias-SG + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-14-esperberto_abdulhade_en.md b/docs/_posts/ahmedlone127/2024-09-14-esperberto_abdulhade_en.md new file mode 100644 index 00000000000000..78943a4a3a6aab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-14-esperberto_abdulhade_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English esperberto_abdulhade RoBertaEmbeddings from abdulhade +author: John Snow Labs +name: esperberto_abdulhade +date: 2024-09-14 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esperberto_abdulhade` is a English model originally trained by abdulhade. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esperberto_abdulhade_en_5.5.0_3.0_1726338001624.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esperberto_abdulhade_en_5.5.0_3.0_1726338001624.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") + +embeddings = RoBertaEmbeddings.pretrained("esperberto_abdulhade","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("esperberto_abdulhade","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esperberto_abdulhade| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|310.2 MB| + +## References + +https://huggingface.co/abdulhade/EsperBERTo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-14-riskanalysis_albert_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-14-riskanalysis_albert_base_v2_pipeline_en.md new file mode 100644 index 00000000000000..62a373a2ccd360 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-14-riskanalysis_albert_base_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English riskanalysis_albert_base_v2_pipeline pipeline AlbertForSequenceClassification from Mahmoud8 +author: John Snow Labs +name: riskanalysis_albert_base_v2_pipeline +date: 2024-09-14 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`riskanalysis_albert_base_v2_pipeline` is a English model originally trained by Mahmoud8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/riskanalysis_albert_base_v2_pipeline_en_5.5.0_3.0_1726309448432.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/riskanalysis_albert_base_v2_pipeline_en_5.5.0_3.0_1726309448432.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("riskanalysis_albert_base_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("riskanalysis_albert_base_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|riskanalysis_albert_base_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/Mahmoud8/RiskAnalysis-albert-base-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-14-whisper_small_few_audios_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-14-whisper_small_few_audios_pipeline_en.md new file mode 100644 index 00000000000000..c1f826b224a285 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-14-whisper_small_few_audios_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_few_audios_pipeline pipeline WhisperForCTC from breco +author: John Snow Labs +name: whisper_small_few_audios_pipeline +date: 2024-09-14 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +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.`whisper_small_few_audios_pipeline` is a English model originally trained by breco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_few_audios_pipeline_en_5.5.0_3.0_1726322094192.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_few_audios_pipeline_en_5.5.0_3.0_1726322094192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_few_audios_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_few_audios_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_few_audios_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/breco/whisper-small-few-audios + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-15-teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline_he.md b/docs/_posts/ahmedlone127/2024-09-15-teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline_he.md new file mode 100644 index 00000000000000..d1863d6bb23439 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-15-teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline_he.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Hebrew teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline pipeline WhisperForCTC from cantillation +author: John Snow Labs +name: teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline +date: 2024-09-15 +tags: [he, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: he +edition: Spark NLP 5.5.0 +spark_version: 3.0 +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.`teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline` is a Hebrew model originally trained by cantillation. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline_he_5.5.0_3.0_1726419635838.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline_he_5.5.0_3.0_1726419635838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline", lang = "he") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline", lang = "he") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|teamim_tiny_weightdecay_0_05_augmented_nepal_bhasa_data_date_10_07_2024_13_20_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|he| +|Size:|390.1 MB| + +## References + +https://huggingface.co/cantillation/Teamim-tiny_WeightDecay-0.05_Augmented_New-Data_date-10-07-2024_13-20 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-16-finetuned_sentiment_model_3000_samples_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-16-finetuned_sentiment_model_3000_samples_pipeline_en.md new file mode 100644 index 00000000000000..7f7ae5888e4cf0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-16-finetuned_sentiment_model_3000_samples_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_sentiment_model_3000_samples_pipeline pipeline BertForSequenceClassification from saran026 +author: John Snow Labs +name: finetuned_sentiment_model_3000_samples_pipeline +date: 2024-09-16 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentiment_model_3000_samples_pipeline` is a English model originally trained by saran026. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_3000_samples_pipeline_en_5.5.0_3.0_1726462726523.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_model_3000_samples_pipeline_en_5.5.0_3.0_1726462726523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_sentiment_model_3000_samples_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_sentiment_model_3000_samples_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sentiment_model_3000_samples_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/saran026/finetuned-sentiment-model-3000-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-17-burmese_awesome_qa_model_203824552xjc_en.md b/docs/_posts/ahmedlone127/2024-09-17-burmese_awesome_qa_model_203824552xjc_en.md new file mode 100644 index 00000000000000..22f8321160e7ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-17-burmese_awesome_qa_model_203824552xjc_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English burmese_awesome_qa_model_203824552xjc DistilBertForQuestionAnswering from 203824552xjc +author: John Snow Labs +name: burmese_awesome_qa_model_203824552xjc +date: 2024-09-17 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_203824552xjc` is a English model originally trained by 203824552xjc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_203824552xjc_en_5.5.0_3.0_1726555720748.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_203824552xjc_en_5.5.0_3.0_1726555720748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_203824552xjc","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_203824552xjc", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_qa_model_203824552xjc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/203824552xjc/my_awesome_qa_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-17-distilbert_base_uncased_finetuned_squad_maxwellmuf_en.md b/docs/_posts/ahmedlone127/2024-09-17-distilbert_base_uncased_finetuned_squad_maxwellmuf_en.md new file mode 100644 index 00000000000000..05ab6c78be0b90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-17-distilbert_base_uncased_finetuned_squad_maxwellmuf_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_squad_maxwellmuf DistilBertForQuestionAnswering from MaxwellmuF +author: John Snow Labs +name: distilbert_base_uncased_finetuned_squad_maxwellmuf +date: 2024-09-17 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_maxwellmuf` is a English model originally trained by MaxwellmuF. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_maxwellmuf_en_5.5.0_3.0_1726599604586.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_maxwellmuf_en_5.5.0_3.0_1726599604586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_maxwellmuf","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_maxwellmuf", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_squad_maxwellmuf| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/MaxwellmuF/distilbert-base-uncased-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-17-xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-17-xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline_en.md new file mode 100644 index 00000000000000..a170b65d9a1428 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-17-xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline pipeline XlmRoBertaForTokenClassification from sirhugh15 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline +date: 2024-09-17 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline` is a English model originally trained by sirhugh15. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline_en_5.5.0_3.0_1726611995401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline_en_5.5.0_3.0_1726611995401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_french_sirhugh15_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|858.2 MB| + +## References + +https://huggingface.co/sirhugh15/xlm-roberta-base-finetuned-panx-de-fr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-18-bert_mlm_armas_inga_estrella_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-18-bert_mlm_armas_inga_estrella_pipeline_en.md new file mode 100644 index 00000000000000..7eadf331efc91c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-18-bert_mlm_armas_inga_estrella_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mlm_armas_inga_estrella_pipeline pipeline BertEmbeddings from JFernandoGRE +author: John Snow Labs +name: bert_mlm_armas_inga_estrella_pipeline +date: 2024-09-18 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mlm_armas_inga_estrella_pipeline` is a English model originally trained by JFernandoGRE. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mlm_armas_inga_estrella_pipeline_en_5.5.0_3.0_1726700503761.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mlm_armas_inga_estrella_pipeline_en_5.5.0_3.0_1726700503761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mlm_armas_inga_estrella_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mlm_armas_inga_estrella_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mlm_armas_inga_estrella_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/JFernandoGRE/bert_mlm_ARMAS_INGA_ESTRELLA + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-18-distilbert_base_uncased_finetuned_emotion_facehugger69420_en.md b/docs/_posts/ahmedlone127/2024-09-18-distilbert_base_uncased_finetuned_emotion_facehugger69420_en.md new file mode 100644 index 00000000000000..492c565ffd1d02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-18-distilbert_base_uncased_finetuned_emotion_facehugger69420_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_facehugger69420 DistilBertForSequenceClassification from FaceHugger69420 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_facehugger69420 +date: 2024-09-18 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_facehugger69420` is a English model originally trained by FaceHugger69420. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_facehugger69420_en_5.5.0_3.0_1726695303971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_facehugger69420_en_5.5.0_3.0_1726695303971.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_facehugger69420","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_facehugger69420", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_facehugger69420| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/FaceHugger69420/distilbert-base-uncased-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-18-distilbert_sentiment_analysis_ellipticcurve_en.md b/docs/_posts/ahmedlone127/2024-09-18-distilbert_sentiment_analysis_ellipticcurve_en.md new file mode 100644 index 00000000000000..77f4193b5f8ad7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-18-distilbert_sentiment_analysis_ellipticcurve_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_sentiment_analysis_ellipticcurve DistilBertForSequenceClassification from EllipticCurve +author: John Snow Labs +name: distilbert_sentiment_analysis_ellipticcurve +date: 2024-09-18 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sentiment_analysis_ellipticcurve` is a English model originally trained by EllipticCurve. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_analysis_ellipticcurve_en_5.5.0_3.0_1726669886194.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sentiment_analysis_ellipticcurve_en_5.5.0_3.0_1726669886194.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 = DistilBertForSequenceClassification.pretrained("distilbert_sentiment_analysis_ellipticcurve","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sentiment_analysis_ellipticcurve", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_sentiment_analysis_ellipticcurve| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/EllipticCurve/DistilBERT-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-18-imdb_4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-18-imdb_4_pipeline_en.md new file mode 100644 index 00000000000000..70016b1a16534e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-18-imdb_4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English imdb_4_pipeline pipeline DistilBertForSequenceClassification from draghicivlad +author: John Snow Labs +name: imdb_4_pipeline +date: 2024-09-18 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_4_pipeline` is a English model originally trained by draghicivlad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_4_pipeline_en_5.5.0_3.0_1726677531940.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_4_pipeline_en_5.5.0_3.0_1726677531940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("imdb_4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("imdb_4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imdb_4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/draghicivlad/imdb_4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-bge_large_eedi_2024_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-19-bge_large_eedi_2024_pipeline_en.md new file mode 100644 index 00000000000000..c118edf8dbb41b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-bge_large_eedi_2024_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_large_eedi_2024_pipeline pipeline BGEEmbeddings from Gurveer05 +author: John Snow Labs +name: bge_large_eedi_2024_pipeline +date: 2024-09-19 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_eedi_2024_pipeline` is a English model originally trained by Gurveer05. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_eedi_2024_pipeline_en_5.5.0_3.0_1726764788871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_eedi_2024_pipeline_en_5.5.0_3.0_1726764788871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_eedi_2024_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_eedi_2024_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_eedi_2024_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Gurveer05/bge-large-eedi-2024 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-category_1_balanced_distilbert_base_uncased_v4_en.md b/docs/_posts/ahmedlone127/2024-09-19-category_1_balanced_distilbert_base_uncased_v4_en.md new file mode 100644 index 00000000000000..60e26cb56555f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-category_1_balanced_distilbert_base_uncased_v4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English category_1_balanced_distilbert_base_uncased_v4 DistilBertForSequenceClassification from chuuhtetnaing +author: John Snow Labs +name: category_1_balanced_distilbert_base_uncased_v4 +date: 2024-09-19 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`category_1_balanced_distilbert_base_uncased_v4` is a English model originally trained by chuuhtetnaing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/category_1_balanced_distilbert_base_uncased_v4_en_5.5.0_3.0_1726763449708.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/category_1_balanced_distilbert_base_uncased_v4_en_5.5.0_3.0_1726763449708.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 = DistilBertForSequenceClassification.pretrained("category_1_balanced_distilbert_base_uncased_v4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("category_1_balanced_distilbert_base_uncased_v4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|category_1_balanced_distilbert_base_uncased_v4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/chuuhtetnaing/category-1-balanced-distilbert-base-uncased-v4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-emotions_en.md b/docs/_posts/ahmedlone127/2024-09-19-emotions_en.md new file mode 100644 index 00000000000000..d97ef22f345946 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-emotions_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English emotions RoBertaForSequenceClassification from HARSHU550 +author: John Snow Labs +name: emotions +date: 2024-09-19 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotions` is a English model originally trained by HARSHU550. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotions_en_5.5.0_3.0_1726733511674.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotions_en_5.5.0_3.0_1726733511674.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 = RoBertaForSequenceClassification.pretrained("emotions","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("emotions", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emotions| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|308.8 MB| + +## References + +https://huggingface.co/HARSHU550/Emotions \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-finetuning_sentiment_model_3000_samples_jamnik99_en.md b/docs/_posts/ahmedlone127/2024-09-19-finetuning_sentiment_model_3000_samples_jamnik99_en.md new file mode 100644 index 00000000000000..60c78f151b84ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-finetuning_sentiment_model_3000_samples_jamnik99_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_jamnik99 DistilBertForSequenceClassification from jamnik99 +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_jamnik99 +date: 2024-09-19 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_jamnik99` is a English model originally trained by jamnik99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jamnik99_en_5.5.0_3.0_1726743199757.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jamnik99_en_5.5.0_3.0_1726743199757.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 = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jamnik99","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jamnik99", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_jamnik99| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/jamnik99/finetuning-sentiment-model-3000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-guaran_bert_tiny_cased_pipeline_gn.md b/docs/_posts/ahmedlone127/2024-09-19-guaran_bert_tiny_cased_pipeline_gn.md new file mode 100644 index 00000000000000..59efc91cc0927f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-guaran_bert_tiny_cased_pipeline_gn.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Guarani guaran_bert_tiny_cased_pipeline pipeline BertEmbeddings from mmaguero +author: John Snow Labs +name: guaran_bert_tiny_cased_pipeline +date: 2024-09-19 +tags: [gn, open_source, pipeline, onnx] +task: Embeddings +language: gn +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`guaran_bert_tiny_cased_pipeline` is a Guarani model originally trained by mmaguero. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/guaran_bert_tiny_cased_pipeline_gn_5.5.0_3.0_1726731794536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/guaran_bert_tiny_cased_pipeline_gn_5.5.0_3.0_1726731794536.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("guaran_bert_tiny_cased_pipeline", lang = "gn") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("guaran_bert_tiny_cased_pipeline", lang = "gn") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|guaran_bert_tiny_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|gn| +|Size:|34.5 MB| + +## References + +https://huggingface.co/mmaguero/gn-bert-tiny-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-legal_longformer_base_8192_spanish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-19-legal_longformer_base_8192_spanish_pipeline_en.md new file mode 100644 index 00000000000000..95f960b18c0b03 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-legal_longformer_base_8192_spanish_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English legal_longformer_base_8192_spanish_pipeline pipeline RoBertaEmbeddings from clibrain +author: John Snow Labs +name: legal_longformer_base_8192_spanish_pipeline +date: 2024-09-19 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_longformer_base_8192_spanish_pipeline` is a English model originally trained by clibrain. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_longformer_base_8192_spanish_pipeline_en_5.5.0_3.0_1726778187932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_longformer_base_8192_spanish_pipeline_en_5.5.0_3.0_1726778187932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legal_longformer_base_8192_spanish_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legal_longformer_base_8192_spanish_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_longformer_base_8192_spanish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|490.7 MB| + +## References + +https://huggingface.co/clibrain/legal-longformer-base-8192-spanish + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-mlm_finetunedmodel_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-19-mlm_finetunedmodel_test_pipeline_en.md new file mode 100644 index 00000000000000..335b9b7954a9d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-mlm_finetunedmodel_test_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mlm_finetunedmodel_test_pipeline pipeline RoBertaEmbeddings from shradha01 +author: John Snow Labs +name: mlm_finetunedmodel_test_pipeline +date: 2024-09-19 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mlm_finetunedmodel_test_pipeline` is a English model originally trained by shradha01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mlm_finetunedmodel_test_pipeline_en_5.5.0_3.0_1726746983313.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mlm_finetunedmodel_test_pipeline_en_5.5.0_3.0_1726746983313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mlm_finetunedmodel_test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mlm_finetunedmodel_test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mlm_finetunedmodel_test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.1 MB| + +## References + +https://huggingface.co/shradha01/MLM_FinetunedModel_test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-roberta_tagalog_base_ft_udpos213_nigerian_pidgin_tl.md b/docs/_posts/ahmedlone127/2024-09-19-roberta_tagalog_base_ft_udpos213_nigerian_pidgin_tl.md new file mode 100644 index 00000000000000..7187a5c2aa304f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-roberta_tagalog_base_ft_udpos213_nigerian_pidgin_tl.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Tagalog roberta_tagalog_base_ft_udpos213_nigerian_pidgin RoBertaForTokenClassification from iceman2434 +author: John Snow Labs +name: roberta_tagalog_base_ft_udpos213_nigerian_pidgin +date: 2024-09-19 +tags: [tl, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: tl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_tagalog_base_ft_udpos213_nigerian_pidgin` is a Tagalog model originally trained by iceman2434. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_tagalog_base_ft_udpos213_nigerian_pidgin_tl_5.5.0_3.0_1726731232430.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_tagalog_base_ft_udpos213_nigerian_pidgin_tl_5.5.0_3.0_1726731232430.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_tagalog_base_ft_udpos213_nigerian_pidgin","tl") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_tagalog_base_ft_udpos213_nigerian_pidgin", "tl") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_tagalog_base_ft_udpos213_nigerian_pidgin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|tl| +|Size:|407.2 MB| + +## References + +https://huggingface.co/iceman2434/roberta-tagalog-base-ft-udpos213-pcm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-19-sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline_en.md new file mode 100644 index 00000000000000..fd4ef2685642fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline pipeline BertSentenceEmbeddings from AethiQs-Max +author: John Snow Labs +name: sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline +date: 2024-09-19 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline` is a English model originally trained by AethiQs-Max. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline_en_5.5.0_3.0_1726783017156.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline_en_5.5.0_3.0_1726783017156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_aethiqs_base_bertje_data_rotterdam_epochs_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/AethiQs-Max/aethiqs-base_bertje-data_rotterdam-epochs_10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-19-sent_bert_large_ct_en.md b/docs/_posts/ahmedlone127/2024-09-19-sent_bert_large_ct_en.md new file mode 100644 index 00000000000000..82e06d5c20cec8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-19-sent_bert_large_ct_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_large_ct BertSentenceEmbeddings from Contrastive-Tension +author: John Snow Labs +name: sent_bert_large_ct +date: 2024-09-19 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_ct` is a English model originally trained by Contrastive-Tension. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_ct_en_5.5.0_3.0_1726728746113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_ct_en_5.5.0_3.0_1726728746113.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_ct","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_ct","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_large_ct| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Contrastive-Tension/BERT-Large-CT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-bert_multiclass_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-20-bert_multiclass_classification_pipeline_en.md new file mode 100644 index 00000000000000..25cedd4f5bd14b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-bert_multiclass_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_multiclass_classification_pipeline pipeline BertForSequenceClassification from Ronysalem +author: John Snow Labs +name: bert_multiclass_classification_pipeline +date: 2024-09-20 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multiclass_classification_pipeline` is a English model originally trained by Ronysalem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multiclass_classification_pipeline_en_5.5.0_3.0_1726797178930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multiclass_classification_pipeline_en_5.5.0_3.0_1726797178930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_multiclass_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_multiclass_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_multiclass_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ronysalem/Bert-Multiclass-Classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-bsc_bio_ehr_spanish_carmen_symptemist_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-20-bsc_bio_ehr_spanish_carmen_symptemist_pipeline_es.md new file mode 100644 index 00000000000000..417966cff6f31a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-bsc_bio_ehr_spanish_carmen_symptemist_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bsc_bio_ehr_spanish_carmen_symptemist_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA +author: John Snow Labs +name: bsc_bio_ehr_spanish_carmen_symptemist_pipeline +date: 2024-09-20 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_carmen_symptemist_pipeline` is a Castilian, Spanish model originally trained by BSC-NLP4BIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_symptemist_pipeline_es_5.5.0_3.0_1726862818355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_carmen_symptemist_pipeline_es_5.5.0_3.0_1726862818355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_carmen_symptemist_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_carmen_symptemist_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bsc_bio_ehr_spanish_carmen_symptemist_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|449.5 MB| + +## References + +https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-carmen-symptemist + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-burmese_model1_en.md b/docs/_posts/ahmedlone127/2024-09-20-burmese_model1_en.md new file mode 100644 index 00000000000000..de722eaedb0831 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-burmese_model1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_model1 DistilBertForSequenceClassification from Asadbek1 +author: John Snow Labs +name: burmese_model1 +date: 2024-09-20 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_model1` is a English model originally trained by Asadbek1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_model1_en_5.5.0_3.0_1726842224182.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_model1_en_5.5.0_3.0_1726842224182.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 = DistilBertForSequenceClassification.pretrained("burmese_model1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_model1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_model1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Asadbek1/my_model1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-convbert_base_generator_finnish_pipeline_fi.md b/docs/_posts/ahmedlone127/2024-09-20-convbert_base_generator_finnish_pipeline_fi.md new file mode 100644 index 00000000000000..6577901ab7f603 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-convbert_base_generator_finnish_pipeline_fi.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Finnish convbert_base_generator_finnish_pipeline pipeline BertEmbeddings from Finnish-NLP +author: John Snow Labs +name: convbert_base_generator_finnish_pipeline +date: 2024-09-20 +tags: [fi, open_source, pipeline, onnx] +task: Embeddings +language: fi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`convbert_base_generator_finnish_pipeline` is a Finnish model originally trained by Finnish-NLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/convbert_base_generator_finnish_pipeline_fi_5.5.0_3.0_1726806379722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/convbert_base_generator_finnish_pipeline_fi_5.5.0_3.0_1726806379722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("convbert_base_generator_finnish_pipeline", lang = "fi") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("convbert_base_generator_finnish_pipeline", lang = "fi") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|convbert_base_generator_finnish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fi| +|Size:|181.3 MB| + +## References + +https://huggingface.co/Finnish-NLP/convbert-base-generator-finnish + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-distilbert_base_uncased_finetuned_emotion_awayes_en.md b/docs/_posts/ahmedlone127/2024-09-20-distilbert_base_uncased_finetuned_emotion_awayes_en.md new file mode 100644 index 00000000000000..223856ce5be5cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-distilbert_base_uncased_finetuned_emotion_awayes_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_awayes DistilBertForSequenceClassification from Awayes +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_awayes +date: 2024-09-20 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_awayes` is a English model originally trained by Awayes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_awayes_en_5.5.0_3.0_1726860903958.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_awayes_en_5.5.0_3.0_1726860903958.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_awayes","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_awayes", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_awayes| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Awayes/distilbert-base-uncased-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted_en.md b/docs/_posts/ahmedlone127/2024-09-20-distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted_en.md new file mode 100644 index 00000000000000..a8d8ed7438f4d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted DistilBertForSequenceClassification from ben-yu +author: John Snow Labs +name: distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted +date: 2024-09-20 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted` is a English model originally trained by ben-yu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted_en_5.5.0_3.0_1726809639436.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted_en_5.5.0_3.0_1726809639436.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_nlp_letters_s1_s2_all_class_weighted| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/ben-yu/distilbert-base-uncased-finetuned-nlp-letters-s1_s2-all-class-weighted \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007_en.md b/docs/_posts/ahmedlone127/2024-09-20-finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007_en.md new file mode 100644 index 00000000000000..03b384a7f539b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007 DistilBertForSequenceClassification from rahulgaikwad007 +author: John Snow Labs +name: finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007 +date: 2024-09-20 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007` is a English model originally trained by rahulgaikwad007. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007_en_5.5.0_3.0_1726842561031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007_en_5.5.0_3.0_1726842561031.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 = DistilBertForSequenceClassification.pretrained("finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_imdb_sentiment_model_3000_samples_rahulgaikwad007| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/rahulgaikwad007/finetuning-imdb-sentiment-model-3000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-finetuning_sentiment_model_300_samples_kanzabatool_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-20-finetuning_sentiment_model_300_samples_kanzabatool_pipeline_en.md new file mode 100644 index 00000000000000..9a8e2eae69e9dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-finetuning_sentiment_model_300_samples_kanzabatool_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_sentiment_model_300_samples_kanzabatool_pipeline pipeline DistilBertForSequenceClassification from KanzaBatool +author: John Snow Labs +name: finetuning_sentiment_model_300_samples_kanzabatool_pipeline +date: 2024-09-20 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_300_samples_kanzabatool_pipeline` is a English model originally trained by KanzaBatool. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_300_samples_kanzabatool_pipeline_en_5.5.0_3.0_1726824094880.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_300_samples_kanzabatool_pipeline_en_5.5.0_3.0_1726824094880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_sentiment_model_300_samples_kanzabatool_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_sentiment_model_300_samples_kanzabatool_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_300_samples_kanzabatool_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/KanzaBatool/finetuning-sentiment-model-300-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-llm_b_hw001_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-20-llm_b_hw001_pipeline_en.md new file mode 100644 index 00000000000000..d547ecf89d1bdc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-llm_b_hw001_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English llm_b_hw001_pipeline pipeline DistilBertForSequenceClassification from Chungyeh +author: John Snow Labs +name: llm_b_hw001_pipeline +date: 2024-09-20 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llm_b_hw001_pipeline` is a English model originally trained by Chungyeh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llm_b_hw001_pipeline_en_5.5.0_3.0_1726809115719.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llm_b_hw001_pipeline_en_5.5.0_3.0_1726809115719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("llm_b_hw001_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("llm_b_hw001_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llm_b_hw001_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Chungyeh/LLM_B_HW001 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-model_jbinek_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-20-model_jbinek_pipeline_en.md new file mode 100644 index 00000000000000..c46de192343255 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-model_jbinek_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_jbinek_pipeline pipeline RoBertaForSequenceClassification from jbinek +author: John Snow Labs +name: model_jbinek_pipeline +date: 2024-09-20 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_jbinek_pipeline` is a English model originally trained by jbinek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_jbinek_pipeline_en_5.5.0_3.0_1726851982311.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_jbinek_pipeline_en_5.5.0_3.0_1726851982311.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_jbinek_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_jbinek_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_jbinek_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|416.4 MB| + +## References + +https://huggingface.co/jbinek/model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-roberta_base_disaster_tweets_downpour_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-20-roberta_base_disaster_tweets_downpour_pipeline_en.md new file mode 100644 index 00000000000000..13a028d6e9f8c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-roberta_base_disaster_tweets_downpour_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_disaster_tweets_downpour_pipeline pipeline RoBertaForSequenceClassification from maxschlake +author: John Snow Labs +name: roberta_base_disaster_tweets_downpour_pipeline +date: 2024-09-20 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_disaster_tweets_downpour_pipeline` is a English model originally trained by maxschlake. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_disaster_tweets_downpour_pipeline_en_5.5.0_3.0_1726851630394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_disaster_tweets_downpour_pipeline_en_5.5.0_3.0_1726851630394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_disaster_tweets_downpour_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_disaster_tweets_downpour_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_disaster_tweets_downpour_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|444.9 MB| + +## References + +https://huggingface.co/maxschlake/roberta-base_disaster_tweets_downpour + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-roberta_large_finetuned_combined_ds_en.md b/docs/_posts/ahmedlone127/2024-09-20-roberta_large_finetuned_combined_ds_en.md new file mode 100644 index 00000000000000..008bf5c24a5b15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-roberta_large_finetuned_combined_ds_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_finetuned_combined_ds RoBertaForSequenceClassification from IIIT-L +author: John Snow Labs +name: roberta_large_finetuned_combined_ds +date: 2024-09-20 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_combined_ds` is a English model originally trained by IIIT-L. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_combined_ds_en_5.5.0_3.0_1726850754017.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_combined_ds_en_5.5.0_3.0_1726850754017.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 = RoBertaForSequenceClassification.pretrained("roberta_large_finetuned_combined_ds","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("roberta_large_finetuned_combined_ds", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_finetuned_combined_ds| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/IIIT-L/roberta-large-finetuned-combined-DS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-scam_detection_zelchy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-20-scam_detection_zelchy_pipeline_en.md new file mode 100644 index 00000000000000..5fb8b215b99677 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-scam_detection_zelchy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English scam_detection_zelchy_pipeline pipeline BertForSequenceClassification from zelchy +author: John Snow Labs +name: scam_detection_zelchy_pipeline +date: 2024-09-20 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scam_detection_zelchy_pipeline` is a English model originally trained by zelchy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scam_detection_zelchy_pipeline_en_5.5.0_3.0_1726829053033.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scam_detection_zelchy_pipeline_en_5.5.0_3.0_1726829053033.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scam_detection_zelchy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scam_detection_zelchy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scam_detection_zelchy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/zelchy/scam-detection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-sent_bert_base_bookcorpus_en.md b/docs/_posts/ahmedlone127/2024-09-20-sent_bert_base_bookcorpus_en.md new file mode 100644 index 00000000000000..696c334bf212fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-sent_bert_base_bookcorpus_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_base_bookcorpus BertSentenceEmbeddings from AiresPucrs +author: John Snow Labs +name: sent_bert_base_bookcorpus +date: 2024-09-20 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_bookcorpus` is a English model originally trained by AiresPucrs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_bookcorpus_en_5.5.0_3.0_1726868308075.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_bookcorpus_en_5.5.0_3.0_1726868308075.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_bookcorpus","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_bookcorpus","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_bookcorpus| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.3 MB| + +## References + +https://huggingface.co/AiresPucrs/bert-base-bookcorpus \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-20-twitter_roberta_base_mar2021_en.md b/docs/_posts/ahmedlone127/2024-09-20-twitter_roberta_base_mar2021_en.md new file mode 100644 index 00000000000000..13f6cdf3b6b346 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-20-twitter_roberta_base_mar2021_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English twitter_roberta_base_mar2021 RoBertaEmbeddings from cardiffnlp +author: John Snow Labs +name: twitter_roberta_base_mar2021 +date: 2024-09-20 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_roberta_base_mar2021` is a English model originally trained by cardiffnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_mar2021_en_5.5.0_3.0_1726816143162.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_roberta_base_mar2021_en_5.5.0_3.0_1726816143162.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") + +embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_mar2021","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("twitter_roberta_base_mar2021","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_roberta_base_mar2021| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.1 MB| + +## References + +https://huggingface.co/cardiffnlp/twitter-roberta-base-mar2021 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20_en.md b/docs/_posts/ahmedlone127/2024-09-21-bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20_en.md new file mode 100644 index 00000000000000..1a3a62f38d4514 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20 BertForQuestionAnswering from danielkty22 +author: John Snow Labs +name: bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20 +date: 2024-09-21 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +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_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20` is a English model originally trained by danielkty22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20_en_5.5.0_3.0_1726946321090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20_en_5.5.0_3.0_1726946321090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetune_squad_ep_1_0_lr_8e_07_wd_0_08_dp_0_6_swati_20| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-1.0-lr-8e-07-wd-0.08-dp-0.6-ss-20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-distilbert4_en.md b/docs/_posts/ahmedlone127/2024-09-21-distilbert4_en.md new file mode 100644 index 00000000000000..03636540619040 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-distilbert4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert4 DistilBertForSequenceClassification from deptage +author: John Snow Labs +name: distilbert4 +date: 2024-09-21 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert4` is a English model originally trained by deptage. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert4_en_5.5.0_3.0_1726953667557.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert4_en_5.5.0_3.0_1726953667557.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 = DistilBertForSequenceClassification.pretrained("distilbert4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/deptage/distilbert4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp_en.md b/docs/_posts/ahmedlone127/2024-09-21-distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp_en.md new file mode 100644 index 00000000000000..c6fd88a9fc3d1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp DistilBertForSequenceClassification from tom192180 +author: John Snow Labs +name: distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp +date: 2024-09-21 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp` is a English model originally trained by tom192180. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp_en_5.5.0_3.0_1726923907583.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp_en_5.5.0_3.0_1726923907583.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_banking_zphr_0st72_ut52ut1_plain_simsp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/tom192180/distilbert-base-uncased_banking_zphr_0st72_ut52ut1_plain_simsp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-distilbert_base_uncased_finetuned_language_en.md b/docs/_posts/ahmedlone127/2024-09-21-distilbert_base_uncased_finetuned_language_en.md new file mode 100644 index 00000000000000..da91b1cc3638ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-distilbert_base_uncased_finetuned_language_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_language DistilBertForSequenceClassification from davidliu0716 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_language +date: 2024-09-21 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_language` is a English model originally trained by davidliu0716. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_language_en_5.5.0_3.0_1726924097747.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_language_en_5.5.0_3.0_1726924097747.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_language","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_language", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_language| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/davidliu0716/distilbert-base-uncased-finetuned-language \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-fine_tuned_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-21-fine_tuned_distilbert_en.md new file mode 100644 index 00000000000000..d677f5668400e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-fine_tuned_distilbert_en.md @@ -0,0 +1,88 @@ +--- +layout: model +title: English fine_tuned_distilbert DistilBertForQuestionAnswering from Roamify +author: John Snow Labs +name: fine_tuned_distilbert +date: 2024-09-21 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_distilbert` is a English model originally trained by Roamify. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_en_5.5.0_3.0_1726924123097.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_distilbert_en_5.5.0_3.0_1726924123097.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("fine_tuned_distilbert","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) +``` +```scala +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("fine_tuned_distilbert", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_distilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +References + +https://huggingface.co/Roamify/fine-tuned-distilbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-hraf_multilabel_hierarchical_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-21-hraf_multilabel_hierarchical_pipeline_en.md new file mode 100644 index 00000000000000..c36b9b58e3a364 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-hraf_multilabel_hierarchical_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hraf_multilabel_hierarchical_pipeline pipeline DistilBertForSequenceClassification from Chantland +author: John Snow Labs +name: hraf_multilabel_hierarchical_pipeline +date: 2024-09-21 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hraf_multilabel_hierarchical_pipeline` is a English model originally trained by Chantland. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hraf_multilabel_hierarchical_pipeline_en_5.5.0_3.0_1726953484307.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hraf_multilabel_hierarchical_pipeline_en_5.5.0_3.0_1726953484307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hraf_multilabel_hierarchical_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hraf_multilabel_hierarchical_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hraf_multilabel_hierarchical_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Chantland/HRAF_MultiLabel_Hierarchical + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-roberta_base_wechsel_french_fr.md b/docs/_posts/ahmedlone127/2024-09-21-roberta_base_wechsel_french_fr.md new file mode 100644 index 00000000000000..7d249e31461a4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-roberta_base_wechsel_french_fr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: French roberta_base_wechsel_french RoBertaEmbeddings from benjamin +author: John Snow Labs +name: roberta_base_wechsel_french +date: 2024-09-21 +tags: [fr, open_source, onnx, embeddings, roberta] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_wechsel_french` is a French model originally trained by benjamin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_wechsel_french_fr_5.5.0_3.0_1726882575815.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_wechsel_french_fr_5.5.0_3.0_1726882575815.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") + +embeddings = RoBertaEmbeddings.pretrained("roberta_base_wechsel_french","fr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_base_wechsel_french","fr") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_wechsel_french| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|fr| +|Size:|465.7 MB| + +## References + +https://huggingface.co/benjamin/roberta-base-wechsel-french \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-whisper_small_divehi_arch4ngel_dv.md b/docs/_posts/ahmedlone127/2024-09-21-whisper_small_divehi_arch4ngel_dv.md new file mode 100644 index 00000000000000..b1ba41a86c8ca9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-whisper_small_divehi_arch4ngel_dv.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Dhivehi, Divehi, Maldivian whisper_small_divehi_arch4ngel WhisperForCTC from Arch4ngel +author: John Snow Labs +name: whisper_small_divehi_arch4ngel +date: 2024-09-21 +tags: [dv, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: dv +edition: Spark NLP 5.5.0 +spark_version: 3.0 +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.`whisper_small_divehi_arch4ngel` is a Dhivehi, Divehi, Maldivian model originally trained by Arch4ngel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_divehi_arch4ngel_dv_5.5.0_3.0_1726906235064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_divehi_arch4ngel_dv_5.5.0_3.0_1726906235064.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("whisper_small_divehi_arch4ngel","dv") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_divehi_arch4ngel", "dv") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_divehi_arch4ngel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|dv| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Arch4ngel/whisper-small-dv \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-21-whisper_small_russian_lorenzoncina_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-21-whisper_small_russian_lorenzoncina_pipeline_ru.md new file mode 100644 index 00000000000000..34e13230d0ecb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-21-whisper_small_russian_lorenzoncina_pipeline_ru.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Russian whisper_small_russian_lorenzoncina_pipeline pipeline WhisperForCTC from lorenzoncina +author: John Snow Labs +name: whisper_small_russian_lorenzoncina_pipeline +date: 2024-09-21 +tags: [ru, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +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.`whisper_small_russian_lorenzoncina_pipeline` is a Russian model originally trained by lorenzoncina. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_russian_lorenzoncina_pipeline_ru_5.5.0_3.0_1726939330773.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_russian_lorenzoncina_pipeline_ru_5.5.0_3.0_1726939330773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_russian_lorenzoncina_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_russian_lorenzoncina_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_russian_lorenzoncina_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|1.7 GB| + +## References + +https://huggingface.co/lorenzoncina/whisper-small-ru + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-22-bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline_en.md new file mode 100644 index 00000000000000..b0de1ef3a5e663 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline pipeline BertForQuestionAnswering from ozlemsenel +author: John Snow Labs +name: bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline +date: 2024-09-22 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline` is a English model originally trained by ozlemsenel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline_en_5.5.0_3.0_1727049347270.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_ozlemsenel_pipeline_en_5.5.0_3.0_1727049347270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_whole_word_masking_finetuned_squad_ozlemsenel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ozlemsenel/bert-large-uncased-whole-word-masking-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-burmese_fine_tuned_distilbert_lr_1e_05_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-22-burmese_fine_tuned_distilbert_lr_1e_05_pipeline_en.md new file mode 100644 index 00000000000000..4d329ad3ffdd40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-burmese_fine_tuned_distilbert_lr_1e_05_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_fine_tuned_distilbert_lr_1e_05_pipeline pipeline DistilBertForSequenceClassification from Benuehlinger +author: John Snow Labs +name: burmese_fine_tuned_distilbert_lr_1e_05_pipeline +date: 2024-09-22 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_fine_tuned_distilbert_lr_1e_05_pipeline` is a English model originally trained by Benuehlinger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_fine_tuned_distilbert_lr_1e_05_pipeline_en_5.5.0_3.0_1727020907174.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_fine_tuned_distilbert_lr_1e_05_pipeline_en_5.5.0_3.0_1727020907174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_fine_tuned_distilbert_lr_1e_05_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_fine_tuned_distilbert_lr_1e_05_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_fine_tuned_distilbert_lr_1e_05_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Benuehlinger/my-fine-tuned-distilbert-lr-1e-05 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-crossencoder_airline_refine_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-22-crossencoder_airline_refine_pipeline_en.md new file mode 100644 index 00000000000000..00b6499aa43ec2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-crossencoder_airline_refine_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English crossencoder_airline_refine_pipeline pipeline RoBertaForSequenceClassification from srmishra +author: John Snow Labs +name: crossencoder_airline_refine_pipeline +date: 2024-09-22 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`crossencoder_airline_refine_pipeline` is a English model originally trained by srmishra. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/crossencoder_airline_refine_pipeline_en_5.5.0_3.0_1727017450898.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/crossencoder_airline_refine_pipeline_en_5.5.0_3.0_1727017450898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("crossencoder_airline_refine_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("crossencoder_airline_refine_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|crossencoder_airline_refine_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/srmishra/crossencoder-airline-refine + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-distilbert_base_uncased_linasaba_en.md b/docs/_posts/ahmedlone127/2024-09-22-distilbert_base_uncased_linasaba_en.md new file mode 100644 index 00000000000000..258fc8be9f021b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-distilbert_base_uncased_linasaba_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_linasaba BertForSequenceClassification from LinaSaba +author: John Snow Labs +name: distilbert_base_uncased_linasaba +date: 2024-09-22 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_linasaba` is a English model originally trained by LinaSaba. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_linasaba_en_5.5.0_3.0_1727007534551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_linasaba_en_5.5.0_3.0_1727007534551.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("distilbert_base_uncased_linasaba","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("distilbert_base_uncased_linasaba", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_linasaba| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/LinaSaba/distilbert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-distilroberta_base_finetuned_leftarticles_mlm_epochier_en.md b/docs/_posts/ahmedlone127/2024-09-22-distilroberta_base_finetuned_leftarticles_mlm_epochier_en.md new file mode 100644 index 00000000000000..c0e5cfe284b77d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-distilroberta_base_finetuned_leftarticles_mlm_epochier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilroberta_base_finetuned_leftarticles_mlm_epochier RoBertaEmbeddings from happybusinessperson +author: John Snow Labs +name: distilroberta_base_finetuned_leftarticles_mlm_epochier +date: 2024-09-22 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberta_base_finetuned_leftarticles_mlm_epochier` is a English model originally trained by happybusinessperson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_leftarticles_mlm_epochier_en_5.5.0_3.0_1726999926843.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberta_base_finetuned_leftarticles_mlm_epochier_en_5.5.0_3.0_1726999926843.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") + +embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_finetuned_leftarticles_mlm_epochier","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("distilroberta_base_finetuned_leftarticles_mlm_epochier","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberta_base_finetuned_leftarticles_mlm_epochier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|306.5 MB| + +## References + +https://huggingface.co/happybusinessperson/distilroberta-base-finetuned-leftarticles-mlm-epochier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-frugalscore_medium_deberta_bert_score_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-22-frugalscore_medium_deberta_bert_score_pipeline_en.md new file mode 100644 index 00000000000000..14949111d37830 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-frugalscore_medium_deberta_bert_score_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English frugalscore_medium_deberta_bert_score_pipeline pipeline BertForSequenceClassification from moussaKam +author: John Snow Labs +name: frugalscore_medium_deberta_bert_score_pipeline +date: 2024-09-22 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frugalscore_medium_deberta_bert_score_pipeline` is a English model originally trained by moussaKam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frugalscore_medium_deberta_bert_score_pipeline_en_5.5.0_3.0_1727031993467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frugalscore_medium_deberta_bert_score_pipeline_en_5.5.0_3.0_1727031993467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("frugalscore_medium_deberta_bert_score_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("frugalscore_medium_deberta_bert_score_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|frugalscore_medium_deberta_bert_score_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|155.2 MB| + +## References + +https://huggingface.co/moussaKam/frugalscore_medium_deberta_bert-score + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-hindi_codemixed_abusive_muril_en.md b/docs/_posts/ahmedlone127/2024-09-22-hindi_codemixed_abusive_muril_en.md new file mode 100644 index 00000000000000..2bfccf9bc3c678 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-hindi_codemixed_abusive_muril_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hindi_codemixed_abusive_muril BertForSequenceClassification from Hate-speech-CNERG +author: John Snow Labs +name: hindi_codemixed_abusive_muril +date: 2024-09-22 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_codemixed_abusive_muril` is a English model originally trained by Hate-speech-CNERG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hindi_codemixed_abusive_muril_en_5.5.0_3.0_1727032197227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindi_codemixed_abusive_muril_en_5.5.0_3.0_1727032197227.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("hindi_codemixed_abusive_muril","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hindi_codemixed_abusive_muril", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hindi_codemixed_abusive_muril| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|892.6 MB| + +## References + +https://huggingface.co/Hate-speech-CNERG/hindi-codemixed-abusive-MuRIL \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-mentalroberta_empai_final2_en.md b/docs/_posts/ahmedlone127/2024-09-22-mentalroberta_empai_final2_en.md new file mode 100644 index 00000000000000..ca3551deb724af --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-mentalroberta_empai_final2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mentalroberta_empai_final2 RoBertaEmbeddings from LuangMV97 +author: John Snow Labs +name: mentalroberta_empai_final2 +date: 2024-09-22 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mentalroberta_empai_final2` is a English model originally trained by LuangMV97. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mentalroberta_empai_final2_en_5.5.0_3.0_1726999351644.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mentalroberta_empai_final2_en_5.5.0_3.0_1726999351644.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") + +embeddings = RoBertaEmbeddings.pretrained("mentalroberta_empai_final2","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("mentalroberta_empai_final2","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mentalroberta_empai_final2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.0 MB| + +## References + +https://huggingface.co/LuangMV97/MentalRoBERTa_EmpAI_final2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-nlp2_base_3e_4_fixed_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-22-nlp2_base_3e_4_fixed_pipeline_en.md new file mode 100644 index 00000000000000..2888cd33e8d201 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-nlp2_base_3e_4_fixed_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nlp2_base_3e_4_fixed_pipeline pipeline DistilBertForSequenceClassification from VRT-2428211 +author: John Snow Labs +name: nlp2_base_3e_4_fixed_pipeline +date: 2024-09-22 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp2_base_3e_4_fixed_pipeline` is a English model originally trained by VRT-2428211. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp2_base_3e_4_fixed_pipeline_en_5.5.0_3.0_1727033727339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp2_base_3e_4_fixed_pipeline_en_5.5.0_3.0_1727033727339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nlp2_base_3e_4_fixed_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nlp2_base_3e_4_fixed_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp2_base_3e_4_fixed_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/VRT-2428211/NLP2_Base_3e-4_Fixed + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-platzi_distilroberta_base_mrpc_glue_angrim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-22-platzi_distilroberta_base_mrpc_glue_angrim_pipeline_en.md new file mode 100644 index 00000000000000..eea7b79f93c45e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-platzi_distilroberta_base_mrpc_glue_angrim_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English platzi_distilroberta_base_mrpc_glue_angrim_pipeline pipeline RoBertaForSequenceClassification from platzi +author: John Snow Labs +name: platzi_distilroberta_base_mrpc_glue_angrim_pipeline +date: 2024-09-22 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`platzi_distilroberta_base_mrpc_glue_angrim_pipeline` is a English model originally trained by platzi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_angrim_pipeline_en_5.5.0_3.0_1727027164181.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_angrim_pipeline_en_5.5.0_3.0_1727027164181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("platzi_distilroberta_base_mrpc_glue_angrim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("platzi_distilroberta_base_mrpc_glue_angrim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|platzi_distilroberta_base_mrpc_glue_angrim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|308.6 MB| + +## References + +https://huggingface.co/platzi/platzi-distilroberta-base-mrpc-glue-angrim + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-qnli_roberta_base_seed_3_en.md b/docs/_posts/ahmedlone127/2024-09-22-qnli_roberta_base_seed_3_en.md new file mode 100644 index 00000000000000..20102ed5d0b74d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-qnli_roberta_base_seed_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English qnli_roberta_base_seed_3 RoBertaForSequenceClassification from utahnlp +author: John Snow Labs +name: qnli_roberta_base_seed_3 +date: 2024-09-22 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qnli_roberta_base_seed_3` is a English model originally trained by utahnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qnli_roberta_base_seed_3_en_5.5.0_3.0_1727037168279.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qnli_roberta_base_seed_3_en_5.5.0_3.0_1727037168279.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 = RoBertaForSequenceClassification.pretrained("qnli_roberta_base_seed_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("qnli_roberta_base_seed_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qnli_roberta_base_seed_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|461.6 MB| + +## References + +https://huggingface.co/utahnlp/qnli_roberta-base_seed-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-roberta_ingredients_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-22-roberta_ingredients_pipeline_en.md new file mode 100644 index 00000000000000..b334de2257724b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-roberta_ingredients_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_ingredients_pipeline pipeline RoBertaEmbeddings from ggilley +author: John Snow Labs +name: roberta_ingredients_pipeline +date: 2024-09-22 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_ingredients_pipeline` is a English model originally trained by ggilley. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_ingredients_pipeline_en_5.5.0_3.0_1727042099094.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_ingredients_pipeline_en_5.5.0_3.0_1727042099094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_ingredients_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_ingredients_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_ingredients_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.0 MB| + +## References + +https://huggingface.co/ggilley/roberta-ingredients + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-romansh_prima_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-22-romansh_prima_pipeline_en.md new file mode 100644 index 00000000000000..8b629d8ee7470c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-romansh_prima_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English romansh_prima_pipeline pipeline RoBertaForSequenceClassification from davidgaofc +author: John Snow Labs +name: romansh_prima_pipeline +date: 2024-09-22 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`romansh_prima_pipeline` is a English model originally trained by davidgaofc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/romansh_prima_pipeline_en_5.5.0_3.0_1727037146576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/romansh_prima_pipeline_en_5.5.0_3.0_1727037146576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("romansh_prima_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("romansh_prima_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|romansh_prima_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|309.0 MB| + +## References + +https://huggingface.co/davidgaofc/RM_prima + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-sent_bert_base_multilingual_cased_finetuned_swahili_xx.md b/docs/_posts/ahmedlone127/2024-09-22-sent_bert_base_multilingual_cased_finetuned_swahili_xx.md new file mode 100644 index 00000000000000..c530b186ab6322 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-sent_bert_base_multilingual_cased_finetuned_swahili_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual sent_bert_base_multilingual_cased_finetuned_swahili BertSentenceEmbeddings from Davlan +author: John Snow Labs +name: sent_bert_base_multilingual_cased_finetuned_swahili +date: 2024-09-22 +tags: [xx, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_multilingual_cased_finetuned_swahili` is a Multilingual model originally trained by Davlan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_cased_finetuned_swahili_xx_5.5.0_3.0_1727001898568.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_multilingual_cased_finetuned_swahili_xx_5.5.0_3.0_1727001898568.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_multilingual_cased_finetuned_swahili","xx") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_multilingual_cased_finetuned_swahili","xx") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_multilingual_cased_finetuned_swahili| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|xx| +|Size:|664.2 MB| + +## References + +https://huggingface.co/Davlan/bert-base-multilingual-cased-finetuned-swahili \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-sent_bert_base_uncased_dstc9_en.md b/docs/_posts/ahmedlone127/2024-09-22-sent_bert_base_uncased_dstc9_en.md new file mode 100644 index 00000000000000..b69f7eeda45f4a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-sent_bert_base_uncased_dstc9_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_base_uncased_dstc9 BertSentenceEmbeddings from wilsontam +author: John Snow Labs +name: sent_bert_base_uncased_dstc9 +date: 2024-09-22 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_dstc9` is a English model originally trained by wilsontam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_dstc9_en_5.5.0_3.0_1727004496652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_dstc9_en_5.5.0_3.0_1727004496652.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_dstc9","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_dstc9","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_uncased_dstc9| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/wilsontam/bert-base-uncased-dstc9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-sharif_pors_bert_base_sharif_qa_en.md b/docs/_posts/ahmedlone127/2024-09-22-sharif_pors_bert_base_sharif_qa_en.md new file mode 100644 index 00000000000000..48380ec8998432 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-sharif_pors_bert_base_sharif_qa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English sharif_pors_bert_base_sharif_qa BertForQuestionAnswering from parsi-ai-nlpclass +author: John Snow Labs +name: sharif_pors_bert_base_sharif_qa +date: 2024-09-22 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +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.`sharif_pors_bert_base_sharif_qa` is a English model originally trained by parsi-ai-nlpclass. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sharif_pors_bert_base_sharif_qa_en_5.5.0_3.0_1727042482518.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sharif_pors_bert_base_sharif_qa_en_5.5.0_3.0_1727042482518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("sharif_pors_bert_base_sharif_qa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("sharif_pors_bert_base_sharif_qa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sharif_pors_bert_base_sharif_qa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|606.5 MB| + +## References + +https://huggingface.co/parsi-ai-nlpclass/Sharif-Pors-bert-base-sharif-qa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-22-whisper_small_hre3_en.md b/docs/_posts/ahmedlone127/2024-09-22-whisper_small_hre3_en.md new file mode 100644 index 00000000000000..2db5634227aeee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-22-whisper_small_hre3_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_small_hre3 WhisperForCTC from ntviet +author: John Snow Labs +name: whisper_small_hre3 +date: 2024-09-22 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +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.`whisper_small_hre3` is a English model originally trained by ntviet. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_hre3_en_5.5.0_3.0_1726995332212.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_hre3_en_5.5.0_3.0_1726995332212.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("whisper_small_hre3","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_hre3", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_hre3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ntviet/whisper-small-hre3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-agnews_padding30model_en.md b/docs/_posts/ahmedlone127/2024-09-23-agnews_padding30model_en.md new file mode 100644 index 00000000000000..3f10b1bf3dbc69 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-agnews_padding30model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English agnews_padding30model DistilBertForSequenceClassification from Realgon +author: John Snow Labs +name: agnews_padding30model +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`agnews_padding30model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/agnews_padding30model_en_5.5.0_3.0_1727059672270.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/agnews_padding30model_en_5.5.0_3.0_1727059672270.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 = DistilBertForSequenceClassification.pretrained("agnews_padding30model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("agnews_padding30model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|agnews_padding30model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Realgon/agnews_padding30model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-aia_hw01_qian_wu_en.md b/docs/_posts/ahmedlone127/2024-09-23-aia_hw01_qian_wu_en.md new file mode 100644 index 00000000000000..90766f0b6e8bad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-aia_hw01_qian_wu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English aia_hw01_qian_wu DistilBertForSequenceClassification from Qian-Wu +author: John Snow Labs +name: aia_hw01_qian_wu +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aia_hw01_qian_wu` is a English model originally trained by Qian-Wu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aia_hw01_qian_wu_en_5.5.0_3.0_1727097120081.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aia_hw01_qian_wu_en_5.5.0_3.0_1727097120081.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 = DistilBertForSequenceClassification.pretrained("aia_hw01_qian_wu","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("aia_hw01_qian_wu", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aia_hw01_qian_wu| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Qian-Wu/AIA_HW01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000_en.md b/docs/_posts/ahmedlone127/2024-09-23-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000_en.md new file mode 100644 index 00000000000000..b36d189a19e889 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000 BertForQuestionAnswering from danielkty22 +author: John Snow Labs +name: bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000 +date: 2024-09-23 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +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_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000` is a English model originally trained by danielkty22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000_en_5.5.0_3.0_1727049705822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000_en_5.5.0_3.0_1727049705822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetune_squad_ep_0_5_lr_1e_06_wd_0_001_dp_0_99999_swati_140000| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-0.5-lr-1e-06-wd-0.001-dp-0.99999-ss-140000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-bert_finetuned_squad_chunwoolee0_en.md b/docs/_posts/ahmedlone127/2024-09-23-bert_finetuned_squad_chunwoolee0_en.md new file mode 100644 index 00000000000000..3baa69438e1372 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-bert_finetuned_squad_chunwoolee0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_finetuned_squad_chunwoolee0 BertForQuestionAnswering from chunwoolee0 +author: John Snow Labs +name: bert_finetuned_squad_chunwoolee0 +date: 2024-09-23 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +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_finetuned_squad_chunwoolee0` is a English model originally trained by chunwoolee0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_chunwoolee0_en_5.5.0_3.0_1727049909508.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_chunwoolee0_en_5.5.0_3.0_1727049909508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_chunwoolee0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_chunwoolee0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_squad_chunwoolee0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/chunwoolee0/bert-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-burmese_awesome_model_fhjhl_en.md b/docs/_posts/ahmedlone127/2024-09-23-burmese_awesome_model_fhjhl_en.md new file mode 100644 index 00000000000000..fe743a81afc953 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-burmese_awesome_model_fhjhl_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_model_fhjhl DistilBertForSequenceClassification from fhjhl +author: John Snow Labs +name: burmese_awesome_model_fhjhl +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_fhjhl` is a English model originally trained by fhjhl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_fhjhl_en_5.5.0_3.0_1727108398414.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_fhjhl_en_5.5.0_3.0_1727108398414.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 = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_fhjhl","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_fhjhl", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_model_fhjhl| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/fhjhl/my_awesome_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-burmese_awesome_model_tsibbett_en.md b/docs/_posts/ahmedlone127/2024-09-23-burmese_awesome_model_tsibbett_en.md new file mode 100644 index 00000000000000..e82a06017baf24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-burmese_awesome_model_tsibbett_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_model_tsibbett DistilBertForSequenceClassification from tsibbett +author: John Snow Labs +name: burmese_awesome_model_tsibbett +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_model_tsibbett` is a English model originally trained by tsibbett. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_tsibbett_en_5.5.0_3.0_1727082290047.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_tsibbett_en_5.5.0_3.0_1727082290047.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 = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_tsibbett","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("burmese_awesome_model_tsibbett", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_model_tsibbett| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/tsibbett/my_awesome_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-comnumpndistilbertv1_big_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-comnumpndistilbertv1_big_pipeline_en.md new file mode 100644 index 00000000000000..152a6ca9128577 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-comnumpndistilbertv1_big_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English comnumpndistilbertv1_big_pipeline pipeline DistilBertForSequenceClassification from abbassix +author: John Snow Labs +name: comnumpndistilbertv1_big_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comnumpndistilbertv1_big_pipeline` is a English model originally trained by abbassix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comnumpndistilbertv1_big_pipeline_en_5.5.0_3.0_1727086767769.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comnumpndistilbertv1_big_pipeline_en_5.5.0_3.0_1727086767769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("comnumpndistilbertv1_big_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("comnumpndistilbertv1_big_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|comnumpndistilbertv1_big_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|250.4 MB| + +## References + +https://huggingface.co/abbassix/ComNumPNdistilBERTv1-big + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova_en.md b/docs/_posts/ahmedlone127/2024-09-23-dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova_en.md new file mode 100644 index 00000000000000..3aa82a2a49c933 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova RoBertaEmbeddings from ltuzova +author: John Snow Labs +name: dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova +date: 2024-09-23 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova` is a English model originally trained by ltuzova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova_en_5.5.0_3.0_1727122103957.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova_en_5.5.0_3.0_1727122103957.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") + +embeddings = RoBertaEmbeddings.pretrained("dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dapt_plus_tapt_helpfulness_base_pretraining_model_ltuzova| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.2 MB| + +## References + +https://huggingface.co/ltuzova/dapt_plus_tapt_helpfulness_base_pretraining_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline_en.md new file mode 100644 index 00000000000000..8ff748a2ce91f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline pipeline DistilBertForSequenceClassification from alkhwarizmi +author: John Snow Labs +name: distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline` is a English model originally trained by alkhwarizmi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline_en_5.5.0_3.0_1727108299434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline_en_5.5.0_3.0_1727108299434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_adl_hw1_alkhwarizmi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.9 MB| + +## References + +https://huggingface.co/alkhwarizmi/distilbert-base-uncased-finetuned-adl_hw1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_aiekek_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_aiekek_en.md new file mode 100644 index 00000000000000..9563dbd9421891 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_aiekek_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_aiekek DistilBertForSequenceClassification from AIEKEK +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_aiekek +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_aiekek` is a English model originally trained by AIEKEK. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_aiekek_en_5.5.0_3.0_1727059236339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_aiekek_en_5.5.0_3.0_1727059236339.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_aiekek","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_aiekek", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_aiekek| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/AIEKEK/distilbert-base-uncased-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_aiekek_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_aiekek_pipeline_en.md new file mode 100644 index 00000000000000..419180e9bbbddb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_aiekek_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_aiekek_pipeline pipeline DistilBertForSequenceClassification from AIEKEK +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_aiekek_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_aiekek_pipeline` is a English model originally trained by AIEKEK. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_aiekek_pipeline_en_5.5.0_3.0_1727059252357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_aiekek_pipeline_en_5.5.0_3.0_1727059252357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_aiekek_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_aiekek_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_aiekek_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/AIEKEK/distilbert-base-uncased-finetuned-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_harukai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_harukai_pipeline_en.md new file mode 100644 index 00000000000000..c9f03fbec0136f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_harukai_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_harukai_pipeline pipeline DistilBertForSequenceClassification from harukai +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_harukai_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_harukai_pipeline` is a English model originally trained by harukai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_harukai_pipeline_en_5.5.0_3.0_1727097333224.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_harukai_pipeline_en_5.5.0_3.0_1727097333224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_harukai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_harukai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_harukai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/harukai/distilbert-base-uncased-finetuned-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline_en.md new file mode 100644 index 00000000000000..e07b11191d621c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline pipeline DistilBertForSequenceClassification from Sharadhonavar +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline` is a English model originally trained by Sharadhonavar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline_en_5.5.0_3.0_1727097288917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline_en_5.5.0_3.0_1727097288917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_sharadhonavar_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Sharadhonavar/distilbert-base-uncased-finetuned-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_m_share_facts_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_m_share_facts_en.md new file mode 100644 index 00000000000000..66ade9df5fdeea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_finetuned_m_share_facts_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_m_share_facts DistilBertForSequenceClassification from Gregorig +author: John Snow Labs +name: distilbert_base_uncased_finetuned_m_share_facts +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_m_share_facts` is a English model originally trained by Gregorig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_m_share_facts_en_5.5.0_3.0_1727082202380.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_m_share_facts_en_5.5.0_3.0_1727082202380.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_m_share_facts","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_m_share_facts", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_m_share_facts| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Gregorig/distilbert-base-uncased-finetuned-m_share_facts \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline_en.md new file mode 100644 index 00000000000000..7393e985a83509 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline pipeline DistilBertForSequenceClassification from tom192180 +author: John Snow Labs +name: distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline` is a English model originally trained by tom192180. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline_en_5.5.0_3.0_1727097389265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline_en_5.5.0_3.0_1727097389265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_odm_zphr_0st16sd_ut12ut1_plprefix0stlarge_simsp100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.7 MB| + +## References + +https://huggingface.co/tom192180/distilbert-base-uncased_odm_zphr_0st16sd_ut12ut1_PLPrefix0stlarge_simsp100 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100_en.md new file mode 100644 index 00000000000000..5a97b2bbd9ed7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100 DistilBertForSequenceClassification from tom192180 +author: John Snow Labs +name: distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100 +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100` is a English model originally trained by tom192180. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100_en_5.5.0_3.0_1727097208988.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100_en_5.5.0_3.0_1727097208988.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_odm_zphr_0st1sd_ut72ut5_plprefix0stlarge_simsp100_clean100| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/tom192180/distilbert-base-uncased_odm_zphr_0st1sd_ut72ut5_PLPrefix0stlarge_simsp100_clean100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st21sd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st21sd_pipeline_en.md new file mode 100644 index 00000000000000..c4821f88fcbc96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st21sd_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_odm_zphr_0st21sd_pipeline pipeline DistilBertForSequenceClassification from tom192180 +author: John Snow Labs +name: distilbert_base_uncased_odm_zphr_0st21sd_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_odm_zphr_0st21sd_pipeline` is a English model originally trained by tom192180. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st21sd_pipeline_en_5.5.0_3.0_1727094115420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st21sd_pipeline_en_5.5.0_3.0_1727094115420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_odm_zphr_0st21sd_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_odm_zphr_0st21sd_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_odm_zphr_0st21sd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.7 MB| + +## References + +https://huggingface.co/tom192180/distilbert-base-uncased_odm_zphr_0st21sd + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline_en.md new file mode 100644 index 00000000000000..5619863341eb7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline pipeline DistilBertForSequenceClassification from tom192180 +author: John Snow Labs +name: distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline` is a English model originally trained by tom192180. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline_en_5.5.0_3.0_1727059662428.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline_en_5.5.0_3.0_1727059662428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_odm_zphr_0st42sd_ut72ut1_plprefix0stlarge41_simsp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.7 MB| + +## References + +https://huggingface.co/tom192180/distilbert-base-uncased_odm_zphr_0st42sd_ut72ut1_PLPrefix0stlarge41_simsp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_ft_sst5_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_ft_sst5_en.md new file mode 100644 index 00000000000000..b30693bf8746cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_ft_sst5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_ft_sst5 DistilBertForSequenceClassification from pablo-chocobar +author: John Snow Labs +name: distilbert_ft_sst5 +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ft_sst5` is a English model originally trained by pablo-chocobar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ft_sst5_en_5.5.0_3.0_1727097133927.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ft_sst5_en_5.5.0_3.0_1727097133927.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 = DistilBertForSequenceClassification.pretrained("distilbert_ft_sst5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_ft_sst5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_ft_sst5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/pablo-chocobar/distilbert-ft-sst5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-distilbert_nbx_all_l_en.md b/docs/_posts/ahmedlone127/2024-09-23-distilbert_nbx_all_l_en.md new file mode 100644 index 00000000000000..040e2aa0e54b58 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-distilbert_nbx_all_l_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_nbx_all_l DistilBertForSequenceClassification from vishnuhaasan +author: John Snow Labs +name: distilbert_nbx_all_l +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_nbx_all_l` is a English model originally trained by vishnuhaasan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_nbx_all_l_en_5.5.0_3.0_1727073517722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_nbx_all_l_en_5.5.0_3.0_1727073517722.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 = DistilBertForSequenceClassification.pretrained("distilbert_nbx_all_l","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_nbx_all_l", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_nbx_all_l| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/vishnuhaasan/distilbert_nbx_all_l \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-fine_tune_whisper_small_sania67_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-fine_tune_whisper_small_sania67_pipeline_en.md new file mode 100644 index 00000000000000..cc060fe4be2067 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-fine_tune_whisper_small_sania67_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tune_whisper_small_sania67_pipeline pipeline WhisperForCTC from Sania67 +author: John Snow Labs +name: fine_tune_whisper_small_sania67_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +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.`fine_tune_whisper_small_sania67_pipeline` is a English model originally trained by Sania67. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_whisper_small_sania67_pipeline_en_5.5.0_3.0_1727076282223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_whisper_small_sania67_pipeline_en_5.5.0_3.0_1727076282223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tune_whisper_small_sania67_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tune_whisper_small_sania67_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_whisper_small_sania67_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Sania67/Fine_tune_whisper_small + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-fine_tuned_decoder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-fine_tuned_decoder_pipeline_en.md new file mode 100644 index 00000000000000..da8b52e465a792 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-fine_tuned_decoder_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_decoder_pipeline pipeline RoBertaEmbeddings from Beijuka +author: John Snow Labs +name: fine_tuned_decoder_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_decoder_pipeline` is a English model originally trained by Beijuka. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_decoder_pipeline_en_5.5.0_3.0_1727056565481.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_decoder_pipeline_en_5.5.0_3.0_1727056565481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_decoder_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_decoder_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_decoder_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.0 MB| + +## References + +https://huggingface.co/Beijuka/fine_tuned_decoder + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-finetuning_sentiment_model_3000_samples_assoboss_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-finetuning_sentiment_model_3000_samples_assoboss_pipeline_en.md new file mode 100644 index 00000000000000..9a3b14d9faabe9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-finetuning_sentiment_model_3000_samples_assoboss_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_assoboss_pipeline pipeline DistilBertForSequenceClassification from assoboss +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_assoboss_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_assoboss_pipeline` is a English model originally trained by assoboss. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_assoboss_pipeline_en_5.5.0_3.0_1727074281560.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_assoboss_pipeline_en_5.5.0_3.0_1727074281560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_assoboss_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_assoboss_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_assoboss_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/assoboss/finetuning-sentiment-model-3000-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-len_pruned_30_model_en.md b/docs/_posts/ahmedlone127/2024-09-23-len_pruned_30_model_en.md new file mode 100644 index 00000000000000..9a9960f396e2c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-len_pruned_30_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English len_pruned_30_model DistilBertForSequenceClassification from andygoh5 +author: John Snow Labs +name: len_pruned_30_model +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`len_pruned_30_model` is a English model originally trained by andygoh5. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/len_pruned_30_model_en_5.5.0_3.0_1727093711752.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/len_pruned_30_model_en_5.5.0_3.0_1727093711752.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 = DistilBertForSequenceClassification.pretrained("len_pruned_30_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("len_pruned_30_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|len_pruned_30_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/andygoh5/len-pruned-30-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-lnm_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-lnm_ner_pipeline_en.md new file mode 100644 index 00000000000000..182f829522dc7e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-lnm_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lnm_ner_pipeline pipeline BertForTokenClassification from suyashmittal +author: John Snow Labs +name: lnm_ner_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lnm_ner_pipeline` is a English model originally trained by suyashmittal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lnm_ner_pipeline_en_5.5.0_3.0_1727129915499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lnm_ner_pipeline_en_5.5.0_3.0_1727129915499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lnm_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lnm_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lnm_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/suyashmittal/lnm-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-roberta_english_financialnews_tuned_en.md b/docs/_posts/ahmedlone127/2024-09-23-roberta_english_financialnews_tuned_en.md new file mode 100644 index 00000000000000..c61212f5ff9321 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-roberta_english_financialnews_tuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_english_financialnews_tuned RoBertaEmbeddings from CCCCC5 +author: John Snow Labs +name: roberta_english_financialnews_tuned +date: 2024-09-23 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_english_financialnews_tuned` is a English model originally trained by CCCCC5. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_english_financialnews_tuned_en_5.5.0_3.0_1727066326441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_english_financialnews_tuned_en_5.5.0_3.0_1727066326441.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") + +embeddings = RoBertaEmbeddings.pretrained("roberta_english_financialnews_tuned","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("roberta_english_financialnews_tuned","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_english_financialnews_tuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|426.0 MB| + +## References + +https://huggingface.co/CCCCC5/RoBERTa_English_FinancialNews_tuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-secondo_modello_en.md b/docs/_posts/ahmedlone127/2024-09-23-secondo_modello_en.md new file mode 100644 index 00000000000000..ccfd4a0b13b8df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-secondo_modello_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English secondo_modello DistilBertForSequenceClassification from soniarocca31 +author: John Snow Labs +name: secondo_modello +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`secondo_modello` is a English model originally trained by soniarocca31. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/secondo_modello_en_5.5.0_3.0_1727074157979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/secondo_modello_en_5.5.0_3.0_1727074157979.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 = DistilBertForSequenceClassification.pretrained("secondo_modello","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("secondo_modello", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|secondo_modello| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.6 MB| + +## References + +https://huggingface.co/soniarocca31/secondo_modello \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-23-sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier_en.md new file mode 100644 index 00000000000000..6404560d7a88e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier BertSentenceEmbeddings from Intel +author: John Snow Labs +name: sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier +date: 2024-09-23 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier` is a English model originally trained by Intel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier_en_5.5.0_3.0_1727105128374.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier_en_5.5.0_3.0_1727105128374.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_uncased_mnli_sparse_70_unstructured_norwegian_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|226.0 MB| + +## References + +https://huggingface.co/Intel/bert-base-uncased-mnli-sparse-70-unstructured-no-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline_en.md new file mode 100644 index 00000000000000..9fd25de782d308 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline pipeline BertSentenceEmbeddings from jojoUla +author: John Snow Labs +name: sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline` is a English model originally trained by jojoUla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline_en_5.5.0_3.0_1727122967640.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline_en_5.5.0_3.0_1727122967640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_fast_14_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/jojoUla/bert-large-cased-sigir-support-refute-no-label-40-2nd-test-LR10-8-fast-14 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-sent_biobert_patent_reference_extraction_en.md b/docs/_posts/ahmedlone127/2024-09-23-sent_biobert_patent_reference_extraction_en.md new file mode 100644 index 00000000000000..0448f40f51b0cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-sent_biobert_patent_reference_extraction_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_biobert_patent_reference_extraction BertSentenceEmbeddings from kaesve +author: John Snow Labs +name: sent_biobert_patent_reference_extraction +date: 2024-09-23 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_biobert_patent_reference_extraction` is a English model originally trained by kaesve. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_biobert_patent_reference_extraction_en_5.5.0_3.0_1727123298415.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_biobert_patent_reference_extraction_en_5.5.0_3.0_1727123298415.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_biobert_patent_reference_extraction","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_biobert_patent_reference_extraction","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_biobert_patent_reference_extraction| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/kaesve/BioBERT_patent_reference_extraction \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-somd_xlm_3stage_stage0_pre_v1_en.md b/docs/_posts/ahmedlone127/2024-09-23-somd_xlm_3stage_stage0_pre_v1_en.md new file mode 100644 index 00000000000000..7f92af6e3aa517 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-somd_xlm_3stage_stage0_pre_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English somd_xlm_3stage_stage0_pre_v1 XlmRoBertaForSequenceClassification from ThuyNT03 +author: John Snow Labs +name: somd_xlm_3stage_stage0_pre_v1 +date: 2024-09-23 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`somd_xlm_3stage_stage0_pre_v1` is a English model originally trained by ThuyNT03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/somd_xlm_3stage_stage0_pre_v1_en_5.5.0_3.0_1727126070695.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/somd_xlm_3stage_stage0_pre_v1_en_5.5.0_3.0_1727126070695.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 = XlmRoBertaForSequenceClassification.pretrained("somd_xlm_3stage_stage0_pre_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("somd_xlm_3stage_stage0_pre_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|somd_xlm_3stage_stage0_pre_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|791.4 MB| + +## References + +https://huggingface.co/ThuyNT03/SOMD-xlm-3stage-stage0-pre-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-whisper_tiny_cb_en.md b/docs/_posts/ahmedlone127/2024-09-23-whisper_tiny_cb_en.md new file mode 100644 index 00000000000000..bf646d2524aec6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-whisper_tiny_cb_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_tiny_cb WhisperForCTC from mikemason +author: John Snow Labs +name: whisper_tiny_cb +date: 2024-09-23 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +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.`whisper_tiny_cb` is a English model originally trained by mikemason. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_cb_en_5.5.0_3.0_1727077602140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_cb_en_5.5.0_3.0_1727077602140.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("whisper_tiny_cb","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_tiny_cb", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_cb| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|394.9 MB| + +## References + +https://huggingface.co/mikemason/whisper-tiny-cb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-23-xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-23-xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline_en.md new file mode 100644 index 00000000000000..78cb5c4c3c706b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-23-xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline pipeline XlmRoBertaForSequenceClassification from vocabtrimmer +author: John Snow Labs +name: xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline +date: 2024-09-23 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline` is a English model originally trained by vocabtrimmer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline_en_5.5.0_3.0_1727126697747.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline_en_5.5.0_3.0_1727126697747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_tweet_sentiment_italian_trimmed_italian_15000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|360.2 MB| + +## References + +https://huggingface.co/vocabtrimmer/xlm-roberta-base-tweet-sentiment-it-trimmed-it-15000 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-albert_test_model_en.md b/docs/_posts/ahmedlone127/2024-09-24-albert_test_model_en.md new file mode 100644 index 00000000000000..bfda952bfd12fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-albert_test_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_test_model DistilBertForSequenceClassification from KalaiselvanD +author: John Snow Labs +name: albert_test_model +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_test_model` is a English model originally trained by KalaiselvanD. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_test_model_en_5.5.0_3.0_1727204777679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_test_model_en_5.5.0_3.0_1727204777679.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 = DistilBertForSequenceClassification.pretrained("albert_test_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("albert_test_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_test_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/KalaiselvanD/albert_test_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-astro_hep_bert_en.md b/docs/_posts/ahmedlone127/2024-09-24-astro_hep_bert_en.md new file mode 100644 index 00000000000000..a8fd9bd8901988 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-astro_hep_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English astro_hep_bert BertEmbeddings from arnosimons +author: John Snow Labs +name: astro_hep_bert +date: 2024-09-24 +tags: [en, open_source, onnx, embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`astro_hep_bert` is a English model originally trained by arnosimons. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/astro_hep_bert_en_5.5.0_3.0_1727158371681.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/astro_hep_bert_en_5.5.0_3.0_1727158371681.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") + +embeddings = BertEmbeddings.pretrained("astro_hep_bert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("astro_hep_bert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|astro_hep_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|404.1 MB| + +## References + +https://huggingface.co/arnosimons/astro-hep-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-bert_base_cased_jennyc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-bert_base_cased_jennyc_pipeline_en.md new file mode 100644 index 00000000000000..c0539c7b6c681c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-bert_base_cased_jennyc_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_base_cased_jennyc_pipeline pipeline BertForQuestionAnswering from jennyc +author: John Snow Labs +name: bert_base_cased_jennyc_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_jennyc_pipeline` is a English model originally trained by jennyc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_jennyc_pipeline_en_5.5.0_3.0_1727175907764.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_jennyc_pipeline_en_5.5.0_3.0_1727175907764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_jennyc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_jennyc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_jennyc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/jennyc/bert-base-cased + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0_en.md b/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0_en.md new file mode 100644 index 00000000000000..a0c65c11b75b55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0 BertForQuestionAnswering from danielkty22 +author: John Snow Labs +name: bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0 +date: 2024-09-24 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +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_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0` is a English model originally trained by danielkty22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0_en_5.5.0_3.0_1727175914484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0_en_5.5.0_3.0_1727175914484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ep_5_02_b_32_lr_1_2e_06_dp_0_3_swati_900_southern_sotho_false_fh_true_hs_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/danielkty22/bert-base-uncased-ep-5.02-b-32-lr-1.2e-06-dp-0.3-ss-900-st-False-fh-True-hs-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline_en.md new file mode 100644 index 00000000000000..76548f902f2092 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline pipeline BertForQuestionAnswering from danielkty22 +author: John Snow Labs +name: bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline` is a English model originally trained by danielkty22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline_en_5.5.0_3.0_1727175972408.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline_en_5.5.0_3.0_1727175972408.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetune_squad_ep_2_0_lr_5e_05_wd_0_001_dp_0_999_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-2.0-lr-5e-05-wd-0.001-dp-0.999 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en.md new file mode 100644 index 00000000000000..a8819dc9a93fce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline pipeline BertForQuestionAnswering from danielkty22 +author: John Snow Labs +name: bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline` is a English model originally trained by danielkty22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.0_3.0_1727175845432.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline_en_5.5.0_3.0_1727175845432.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetune_squad_ep_3_0_lr_1e_06_wd_0_001_dp_0_2_swati_8228_southern_sotho_false_fh_true_hs_666_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/danielkty22/bert-base-uncased-finetune-squad-ep-3.0-lr-1e-06-wd-0.001-dp-0.2-ss-8228-st-False-fh-True-hs-666 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-bert_distilled_twitter_sent140_dataset_hp_optimized_en.md b/docs/_posts/ahmedlone127/2024-09-24-bert_distilled_twitter_sent140_dataset_hp_optimized_en.md new file mode 100644 index 00000000000000..0700e31800238b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-bert_distilled_twitter_sent140_dataset_hp_optimized_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_distilled_twitter_sent140_dataset_hp_optimized DistilBertForSequenceClassification from ArafatBHossain +author: John Snow Labs +name: bert_distilled_twitter_sent140_dataset_hp_optimized +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_distilled_twitter_sent140_dataset_hp_optimized` is a English model originally trained by ArafatBHossain. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_distilled_twitter_sent140_dataset_hp_optimized_en_5.5.0_3.0_1727164378100.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_distilled_twitter_sent140_dataset_hp_optimized_en_5.5.0_3.0_1727164378100.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 = DistilBertForSequenceClassification.pretrained("bert_distilled_twitter_sent140_dataset_hp_optimized","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_distilled_twitter_sent140_dataset_hp_optimized", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_distilled_twitter_sent140_dataset_hp_optimized| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/ArafatBHossain/bert-distilled-twitter-sent140_dataset_hp_optimized \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-bert_large_cased_sclarge_squadscqa1_en.md b/docs/_posts/ahmedlone127/2024-09-24-bert_large_cased_sclarge_squadscqa1_en.md new file mode 100644 index 00000000000000..012ad918976136 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-bert_large_cased_sclarge_squadscqa1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_large_cased_sclarge_squadscqa1 BertForQuestionAnswering from CambridgeMolecularEngineering +author: John Snow Labs +name: bert_large_cased_sclarge_squadscqa1 +date: 2024-09-24 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +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_large_cased_sclarge_squadscqa1` is a English model originally trained by CambridgeMolecularEngineering. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_sclarge_squadscqa1_en_5.5.0_3.0_1727175595544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_sclarge_squadscqa1_en_5.5.0_3.0_1727175595544.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_sclarge_squadscqa1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_sclarge_squadscqa1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_sclarge_squadscqa1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/CambridgeMolecularEngineering/bert-large-cased-sclarge-squadscqa1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-bert_large_cased_squadscqa1_en.md b/docs/_posts/ahmedlone127/2024-09-24-bert_large_cased_squadscqa1_en.md new file mode 100644 index 00000000000000..353bb815c737b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-bert_large_cased_squadscqa1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_large_cased_squadscqa1 BertForQuestionAnswering from CambridgeMolecularEngineering +author: John Snow Labs +name: bert_large_cased_squadscqa1 +date: 2024-09-24 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +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_large_cased_squadscqa1` is a English model originally trained by CambridgeMolecularEngineering. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_squadscqa1_en_5.5.0_3.0_1727175839654.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_squadscqa1_en_5.5.0_3.0_1727175839654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_squadscqa1","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_cased_squadscqa1", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_squadscqa1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/CambridgeMolecularEngineering/bert-large-cased-squadscqa1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-bert_vllm_gemma2b_8_en.md b/docs/_posts/ahmedlone127/2024-09-24-bert_vllm_gemma2b_8_en.md new file mode 100644 index 00000000000000..348ed7819eee25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-bert_vllm_gemma2b_8_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_vllm_gemma2b_8 DistilBertForSequenceClassification from jvelja +author: John Snow Labs +name: bert_vllm_gemma2b_8 +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_vllm_gemma2b_8` is a English model originally trained by jvelja. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_vllm_gemma2b_8_en_5.5.0_3.0_1727154508525.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_vllm_gemma2b_8_en_5.5.0_3.0_1727154508525.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 = DistilBertForSequenceClassification.pretrained("bert_vllm_gemma2b_8","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("bert_vllm_gemma2b_8", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_vllm_gemma2b_8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/jvelja/BERT_vllm-gemma2b_8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-calc_nepal_bhasa_roberta_ep20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-calc_nepal_bhasa_roberta_ep20_pipeline_en.md new file mode 100644 index 00000000000000..f779091e461e89 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-calc_nepal_bhasa_roberta_ep20_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English calc_nepal_bhasa_roberta_ep20_pipeline pipeline RoBertaForTokenClassification from vishruthnath +author: John Snow Labs +name: calc_nepal_bhasa_roberta_ep20_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`calc_nepal_bhasa_roberta_ep20_pipeline` is a English model originally trained by vishruthnath. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/calc_nepal_bhasa_roberta_ep20_pipeline_en_5.5.0_3.0_1727151059001.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/calc_nepal_bhasa_roberta_ep20_pipeline_en_5.5.0_3.0_1727151059001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("calc_nepal_bhasa_roberta_ep20_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("calc_nepal_bhasa_roberta_ep20_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|calc_nepal_bhasa_roberta_ep20_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|422.6 MB| + +## References + +https://huggingface.co/vishruthnath/Calc_new_RoBERTa_ep20 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-camembert_embeddings_Sonny_generic_model_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-24-camembert_embeddings_Sonny_generic_model_pipeline_fr.md new file mode 100644 index 00000000000000..ea02d1561f73d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-camembert_embeddings_Sonny_generic_model_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French camembert_embeddings_Sonny_generic_model_pipeline pipeline CamemBertEmbeddings from Sonny +author: John Snow Labs +name: camembert_embeddings_Sonny_generic_model_pipeline +date: 2024-09-24 +tags: [fr, open_source, pipeline, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_embeddings_Sonny_generic_model_pipeline` is a French model originally trained by Sonny. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_embeddings_Sonny_generic_model_pipeline_fr_5.5.0_3.0_1727210330864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_embeddings_Sonny_generic_model_pipeline_fr_5.5.0_3.0_1727210330864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camembert_embeddings_Sonny_generic_model_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camembert_embeddings_Sonny_generic_model_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_embeddings_Sonny_generic_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|264.0 MB| + +## References + +https://huggingface.co/Sonny/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-chinese_roberta_wwm_ext_large_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-09-24-chinese_roberta_wwm_ext_large_finetuned_ner_en.md new file mode 100644 index 00000000000000..8425385d75eba9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-chinese_roberta_wwm_ext_large_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English chinese_roberta_wwm_ext_large_finetuned_ner BertForTokenClassification from HYM +author: John Snow Labs +name: chinese_roberta_wwm_ext_large_finetuned_ner +date: 2024-09-24 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_roberta_wwm_ext_large_finetuned_ner` is a English model originally trained by HYM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_large_finetuned_ner_en_5.5.0_3.0_1727203690853.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_large_finetuned_ner_en_5.5.0_3.0_1727203690853.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') + +tokenClassifier = BertForTokenClassification.pretrained("chinese_roberta_wwm_ext_large_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("chinese_roberta_wwm_ext_large_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_wwm_ext_large_finetuned_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/HYM/chinese-roberta-wwm-ext-large-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-codebert_java_en.md b/docs/_posts/ahmedlone127/2024-09-24-codebert_java_en.md new file mode 100644 index 00000000000000..45d1c3ecde7abc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-codebert_java_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English codebert_java RoBertaEmbeddings from neulab +author: John Snow Labs +name: codebert_java +date: 2024-09-24 +tags: [en, open_source, onnx, embeddings, roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codebert_java` is a English model originally trained by neulab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codebert_java_en_5.5.0_3.0_1727216291190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codebert_java_en_5.5.0_3.0_1727216291190.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") + +embeddings = RoBertaEmbeddings.pretrained("codebert_java","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = RoBertaEmbeddings.pretrained("codebert_java","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codebert_java| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.0 MB| + +## References + +https://huggingface.co/neulab/codebert-java \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-discourse_model_en.md b/docs/_posts/ahmedlone127/2024-09-24-discourse_model_en.md new file mode 100644 index 00000000000000..ec4c6bc4c7a468 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-discourse_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English discourse_model RoBertaForSequenceClassification from lightcarrieson +author: John Snow Labs +name: discourse_model +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`discourse_model` is a English model originally trained by lightcarrieson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/discourse_model_en_5.5.0_3.0_1727171802429.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/discourse_model_en_5.5.0_3.0_1727171802429.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 = RoBertaForSequenceClassification.pretrained("discourse_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("discourse_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|discourse_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|422.8 MB| + +## References + +https://huggingface.co/lightcarrieson/discourse_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_multilingual_cased_sent_negativo_esp_xx.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_multilingual_cased_sent_negativo_esp_xx.md new file mode 100644 index 00000000000000..e7e27cb8091328 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_multilingual_cased_sent_negativo_esp_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual distilbert_base_multilingual_cased_sent_negativo_esp DistilBertForSequenceClassification from rogelioplatt +author: John Snow Labs +name: distilbert_base_multilingual_cased_sent_negativo_esp +date: 2024-09-24 +tags: [xx, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_multilingual_cased_sent_negativo_esp` is a Multilingual model originally trained by rogelioplatt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_sent_negativo_esp_xx_5.5.0_3.0_1727204928120.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_multilingual_cased_sent_negativo_esp_xx_5.5.0_3.0_1727204928120.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_multilingual_cased_sent_negativo_esp","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_multilingual_cased_sent_negativo_esp", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_multilingual_cased_sent_negativo_esp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|507.6 MB| + +## References + +https://huggingface.co/rogelioplatt/distilbert-base-multilingual-cased-Sent_Negativo_Esp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_finetuned_emotion_saranghae_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_finetuned_emotion_saranghae_en.md new file mode 100644 index 00000000000000..700ec55b091602 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_finetuned_emotion_saranghae_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_saranghae DistilBertForSequenceClassification from Saranghae +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_saranghae +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_saranghae` is a English model originally trained by Saranghae. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_saranghae_en_5.5.0_3.0_1727164259916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_saranghae_en_5.5.0_3.0_1727164259916.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_saranghae","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_finetuned_emotion_saranghae", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_saranghae| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Saranghae/distilbert-base-uncased-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_finetuned_emotion_yukky777_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_finetuned_emotion_yukky777_pipeline_en.md new file mode 100644 index 00000000000000..fd69262132e70f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_finetuned_emotion_yukky777_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_emotion_yukky777_pipeline pipeline DistilBertForSequenceClassification from yukky777 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_emotion_yukky777_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_emotion_yukky777_pipeline` is a English model originally trained by yukky777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_yukky777_pipeline_en_5.5.0_3.0_1727137480930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_emotion_yukky777_pipeline_en_5.5.0_3.0_1727137480930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_yukky777_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_emotion_yukky777_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_emotion_yukky777_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/yukky777/distilbert-base-uncased-finetuned-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd_en.md new file mode 100644 index 00000000000000..00263dd3ec2ea7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd DistilBertForSequenceClassification from tom192180 +author: John Snow Labs +name: distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd` is a English model originally trained by tom192180. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd_en_5.5.0_3.0_1727154370281.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd_en_5.5.0_3.0_1727154370281.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 = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_odm_zphr_0st42sd_ut72ut5_plprefix0stlarge42_simsp_clean4sd| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.6 MB| + +## References + +https://huggingface.co/tom192180/distilbert-base-uncased_odm_zphr_0st42sd_ut72ut5_PLPrefix0stlarge42_simsp_clean4sd \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_essays_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_essays_en.md new file mode 100644 index 00000000000000..5556a27c5a3ce9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_essays_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_essays DistilBertForSequenceClassification from Bimarshad +author: John Snow Labs +name: distilbert_essays +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_essays` is a English model originally trained by Bimarshad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_essays_en_5.5.0_3.0_1727137579813.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_essays_en_5.5.0_3.0_1727137579813.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 = DistilBertForSequenceClassification.pretrained("distilbert_essays","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_essays", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_essays| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Bimarshad/distilbert.essays \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_lr_cosine_epoch_5_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_lr_cosine_epoch_5_en.md new file mode 100644 index 00000000000000..38206cc0c49f9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_lr_cosine_epoch_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_lr_cosine_epoch_5 DistilBertForSequenceClassification from K-kiron +author: John Snow Labs +name: distilbert_lr_cosine_epoch_5 +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_lr_cosine_epoch_5` is a English model originally trained by K-kiron. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_lr_cosine_epoch_5_en_5.5.0_3.0_1727137381944.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_lr_cosine_epoch_5_en_5.5.0_3.0_1727137381944.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 = DistilBertForSequenceClassification.pretrained("distilbert_lr_cosine_epoch_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_lr_cosine_epoch_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_lr_cosine_epoch_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/K-kiron/distilbert-lr-cosine-epoch-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_ndd_html_content_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_ndd_html_content_en.md new file mode 100644 index 00000000000000..77d64090129980 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_ndd_html_content_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_ndd_html_content DistilBertForSequenceClassification from lgk03 +author: John Snow Labs +name: distilbert_ndd_html_content +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_ndd_html_content` is a English model originally trained by lgk03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_ndd_html_content_en_5.5.0_3.0_1727204776275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_ndd_html_content_en_5.5.0_3.0_1727204776275.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 = DistilBertForSequenceClassification.pretrained("distilbert_ndd_html_content","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_ndd_html_content", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_ndd_html_content| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/lgk03/distilBERT-NDD.html.content \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_on_polarity_yelp_reviews_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_on_polarity_yelp_reviews_en.md new file mode 100644 index 00000000000000..387c19fa34a3a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_on_polarity_yelp_reviews_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_on_polarity_yelp_reviews DistilBertForSequenceClassification from BexRedpill +author: John Snow Labs +name: distilbert_on_polarity_yelp_reviews +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_on_polarity_yelp_reviews` is a English model originally trained by BexRedpill. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_on_polarity_yelp_reviews_en_5.5.0_3.0_1727204776146.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_on_polarity_yelp_reviews_en_5.5.0_3.0_1727204776146.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 = DistilBertForSequenceClassification.pretrained("distilbert_on_polarity_yelp_reviews","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_on_polarity_yelp_reviews", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_on_polarity_yelp_reviews| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/BexRedpill/distilbert-on-polarity-yelp-reviews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96_en.md new file mode 100644 index 00000000000000..2404ff782cd55d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96 DistilBertForSequenceClassification from gokuls +author: John Snow Labs +name: distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96 +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96_en_5.5.0_3.0_1727154978113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96_en_5.5.0_3.0_1727154978113.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 = DistilBertForSequenceClassification.pretrained("distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_sanskrit_saskta_glue_experiment_logit_kd_data_aug_mrpc_96| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|25.7 MB| + +## References + +https://huggingface.co/gokuls/distilbert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_96 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_sanskrit_saskta_glue_experiment_stsb_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_sanskrit_saskta_glue_experiment_stsb_en.md new file mode 100644 index 00000000000000..9f7195a70ef8f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_sanskrit_saskta_glue_experiment_stsb_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_sanskrit_saskta_glue_experiment_stsb DistilBertForSequenceClassification from gokuls +author: John Snow Labs +name: distilbert_sanskrit_saskta_glue_experiment_stsb +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_sanskrit_saskta_glue_experiment_stsb` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_sanskrit_saskta_glue_experiment_stsb_en_5.5.0_3.0_1727154961929.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_sanskrit_saskta_glue_experiment_stsb_en_5.5.0_3.0_1727154961929.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 = DistilBertForSequenceClassification.pretrained("distilbert_sanskrit_saskta_glue_experiment_stsb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_sanskrit_saskta_glue_experiment_stsb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_sanskrit_saskta_glue_experiment_stsb| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|250.8 MB| + +## References + +https://huggingface.co/gokuls/distilbert_sa_GLUE_Experiment_stsb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilbert_v1_b_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilbert_v1_b_en.md new file mode 100644 index 00000000000000..ef8d0e1d4477c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilbert_v1_b_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_v1_b DistilBertForSequenceClassification from sheduele +author: John Snow Labs +name: distilbert_v1_b +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_v1_b` is a English model originally trained by sheduele. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_v1_b_en_5.5.0_3.0_1727164398434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_v1_b_en_5.5.0_3.0_1727164398434.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 = DistilBertForSequenceClassification.pretrained("distilbert_v1_b","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("distilbert_v1_b", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_v1_b| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.6 MB| + +## References + +https://huggingface.co/sheduele/distilbert_v1_b \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-distilroberts_base_mrpc_glue_jeraldflowers_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-distilroberts_base_mrpc_glue_jeraldflowers_pipeline_en.md new file mode 100644 index 00000000000000..d67a67898dd8e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-distilroberts_base_mrpc_glue_jeraldflowers_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilroberts_base_mrpc_glue_jeraldflowers_pipeline pipeline RoBertaForSequenceClassification from jeraldflowers +author: John Snow Labs +name: distilroberts_base_mrpc_glue_jeraldflowers_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilroberts_base_mrpc_glue_jeraldflowers_pipeline` is a English model originally trained by jeraldflowers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilroberts_base_mrpc_glue_jeraldflowers_pipeline_en_5.5.0_3.0_1727171265439.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilroberts_base_mrpc_glue_jeraldflowers_pipeline_en_5.5.0_3.0_1727171265439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilroberts_base_mrpc_glue_jeraldflowers_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilroberts_base_mrpc_glue_jeraldflowers_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilroberts_base_mrpc_glue_jeraldflowers_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|308.6 MB| + +## References + +https://huggingface.co/jeraldflowers/distilroberts-base-mrpc-glue-jeraldflowers + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_jbnextnext_en.md b/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_jbnextnext_en.md new file mode 100644 index 00000000000000..436ec959d07d6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_jbnextnext_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_jbnextnext DistilBertForSequenceClassification from jbnextnext +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_jbnextnext +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_jbnextnext` is a English model originally trained by jbnextnext. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jbnextnext_en_5.5.0_3.0_1727155043629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_jbnextnext_en_5.5.0_3.0_1727155043629.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 = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jbnextnext","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_jbnextnext", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_jbnextnext| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/jbnextnext/finetuning-sentiment-model-3000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_pxuan_en.md b/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_pxuan_en.md new file mode 100644 index 00000000000000..2d4c80de1efbe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_pxuan_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_pxuan DistilBertForSequenceClassification from pxuan +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_pxuan +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_pxuan` is a English model originally trained by pxuan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_pxuan_en_5.5.0_3.0_1727137076690.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_pxuan_en_5.5.0_3.0_1727137076690.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 = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_pxuan","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_pxuan", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_pxuan| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/pxuan/finetuning-sentiment-model-3000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_pxuan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_pxuan_pipeline_en.md new file mode 100644 index 00000000000000..1ecca709ca58f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_3000_samples_pxuan_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_pxuan_pipeline pipeline DistilBertForSequenceClassification from pxuan +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_pxuan_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_pxuan_pipeline` is a English model originally trained by pxuan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_pxuan_pipeline_en_5.5.0_3.0_1727137089875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_pxuan_pipeline_en_5.5.0_3.0_1727137089875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_sentiment_model_3000_samples_pxuan_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_sentiment_model_3000_samples_pxuan_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_pxuan_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/pxuan/finetuning-sentiment-model-3000-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_5000_samples_leonardosegurat_en.md b/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_5000_samples_leonardosegurat_en.md new file mode 100644 index 00000000000000..e1a13f2900504c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-finetuning_sentiment_model_5000_samples_leonardosegurat_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_model_5000_samples_leonardosegurat DistilBertForSequenceClassification from leonardosegurat +author: John Snow Labs +name: finetuning_sentiment_model_5000_samples_leonardosegurat +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_5000_samples_leonardosegurat` is a English model originally trained by leonardosegurat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_leonardosegurat_en_5.5.0_3.0_1727137487572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_5000_samples_leonardosegurat_en_5.5.0_3.0_1727137487572.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 = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_5000_samples_leonardosegurat","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("finetuning_sentiment_model_5000_samples_leonardosegurat", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_5000_samples_leonardosegurat| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/leonardosegurat/finetuning-sentiment-model-5000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-hate_hate_balance_random0_seed2_bertweet_large_en.md b/docs/_posts/ahmedlone127/2024-09-24-hate_hate_balance_random0_seed2_bertweet_large_en.md new file mode 100644 index 00000000000000..45fee9f2e42fe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-hate_hate_balance_random0_seed2_bertweet_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hate_hate_balance_random0_seed2_bertweet_large RoBertaForSequenceClassification from tweettemposhift +author: John Snow Labs +name: hate_hate_balance_random0_seed2_bertweet_large +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_hate_balance_random0_seed2_bertweet_large` is a English model originally trained by tweettemposhift. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hate_hate_balance_random0_seed2_bertweet_large_en_5.5.0_3.0_1727171735043.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_hate_balance_random0_seed2_bertweet_large_en_5.5.0_3.0_1727171735043.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 = RoBertaForSequenceClassification.pretrained("hate_hate_balance_random0_seed2_bertweet_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("hate_hate_balance_random0_seed2_bertweet_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hate_hate_balance_random0_seed2_bertweet_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/tweettemposhift/hate-hate_balance_random0_seed2-bertweet-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-hate_hate_temporal_roberta_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-hate_hate_temporal_roberta_large_pipeline_en.md new file mode 100644 index 00000000000000..8fc16bef7d55ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-hate_hate_temporal_roberta_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hate_hate_temporal_roberta_large_pipeline pipeline RoBertaForSequenceClassification from tweettemposhift +author: John Snow Labs +name: hate_hate_temporal_roberta_large_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_hate_temporal_roberta_large_pipeline` is a English model originally trained by tweettemposhift. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hate_hate_temporal_roberta_large_pipeline_en_5.5.0_3.0_1727171230874.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_hate_temporal_roberta_large_pipeline_en_5.5.0_3.0_1727171230874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hate_hate_temporal_roberta_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hate_hate_temporal_roberta_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hate_hate_temporal_roberta_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/tweettemposhift/hate-hate_temporal-roberta-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-mbert_argmining_abstrct_english_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-24-mbert_argmining_abstrct_english_spanish_es.md new file mode 100644 index 00000000000000..54ee53ac8adebe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-mbert_argmining_abstrct_english_spanish_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish mbert_argmining_abstrct_english_spanish BertForTokenClassification from HiTZ +author: John Snow Labs +name: mbert_argmining_abstrct_english_spanish +date: 2024-09-24 +tags: [es, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_argmining_abstrct_english_spanish` is a Castilian, Spanish model originally trained by HiTZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_argmining_abstrct_english_spanish_es_5.5.0_3.0_1727195860875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_argmining_abstrct_english_spanish_es_5.5.0_3.0_1727195860875.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') + +tokenClassifier = BertForTokenClassification.pretrained("mbert_argmining_abstrct_english_spanish","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("mbert_argmining_abstrct_english_spanish", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbert_argmining_abstrct_english_spanish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|665.1 MB| + +## References + +https://huggingface.co/HiTZ/mbert-argmining-abstrct-en-es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-minilm_emotions_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-24-minilm_emotions_finetuned_en.md new file mode 100644 index 00000000000000..f9a1343b1b2179 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-minilm_emotions_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English minilm_emotions_finetuned BertForSequenceClassification from gyesibiney +author: John Snow Labs +name: minilm_emotions_finetuned +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilm_emotions_finetuned` is a English model originally trained by gyesibiney. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilm_emotions_finetuned_en_5.5.0_3.0_1727219004696.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilm_emotions_finetuned_en_5.5.0_3.0_1727219004696.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("minilm_emotions_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("minilm_emotions_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minilm_emotions_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|118.5 MB| + +## References + +https://huggingface.co/gyesibiney/miniLm-emotions-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-minilm_emotions_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-minilm_emotions_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..1c27ad67083c84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-minilm_emotions_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English minilm_emotions_finetuned_pipeline pipeline BertForSequenceClassification from gyesibiney +author: John Snow Labs +name: minilm_emotions_finetuned_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`minilm_emotions_finetuned_pipeline` is a English model originally trained by gyesibiney. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/minilm_emotions_finetuned_pipeline_en_5.5.0_3.0_1727219012995.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/minilm_emotions_finetuned_pipeline_en_5.5.0_3.0_1727219012995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("minilm_emotions_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("minilm_emotions_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|minilm_emotions_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|118.5 MB| + +## References + +https://huggingface.co/gyesibiney/miniLm-emotions-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-mymodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-mymodel_pipeline_en.md new file mode 100644 index 00000000000000..f2bb3c2659af03 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-mymodel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mymodel_pipeline pipeline RoBertaForSequenceClassification from pujing +author: John Snow Labs +name: mymodel_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mymodel_pipeline` is a English model originally trained by pujing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mymodel_pipeline_en_5.5.0_3.0_1727171516080.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mymodel_pipeline_en_5.5.0_3.0_1727171516080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mymodel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mymodel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mymodel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|308.8 MB| + +## References + +https://huggingface.co/pujing/Mymodel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-output_sonyy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-output_sonyy_pipeline_en.md new file mode 100644 index 00000000000000..10bcbb28e35e5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-output_sonyy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English output_sonyy_pipeline pipeline DistilBertForSequenceClassification from sonyy +author: John Snow Labs +name: output_sonyy_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_sonyy_pipeline` is a English model originally trained by sonyy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_sonyy_pipeline_en_5.5.0_3.0_1727164680456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_sonyy_pipeline_en_5.5.0_3.0_1727164680456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("output_sonyy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("output_sonyy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|output_sonyy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/sonyy/output + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline_en.md new file mode 100644 index 00000000000000..0adef3306023ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline pipeline RoBertaForSequenceClassification from willmendoza +author: John Snow Labs +name: platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline` is a English model originally trained by willmendoza. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline_en_5.5.0_3.0_1727167768550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline_en_5.5.0_3.0_1727167768550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|platzi_distilroberta_base_mrpc_glue_will_mendoza_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|308.6 MB| + +## References + +https://huggingface.co/willmendoza/platzi-distilroberta-base-mrpc-glue-will-mendoza + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-repo_31_5_mlops_zh0rg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-repo_31_5_mlops_zh0rg_pipeline_en.md new file mode 100644 index 00000000000000..a7984197e2bb7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-repo_31_5_mlops_zh0rg_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English repo_31_5_mlops_zh0rg_pipeline pipeline DistilBertForSequenceClassification from Zh0rg +author: John Snow Labs +name: repo_31_5_mlops_zh0rg_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`repo_31_5_mlops_zh0rg_pipeline` is a English model originally trained by Zh0rg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/repo_31_5_mlops_zh0rg_pipeline_en_5.5.0_3.0_1727154629702.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/repo_31_5_mlops_zh0rg_pipeline_en_5.5.0_3.0_1727154629702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("repo_31_5_mlops_zh0rg_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("repo_31_5_mlops_zh0rg_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|repo_31_5_mlops_zh0rg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Zh0rg/repo-31-5-MLOps + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-roberta_qa_finetuned_state_en.md b/docs/_posts/ahmedlone127/2024-09-24-roberta_qa_finetuned_state_en.md new file mode 100644 index 00000000000000..7caa4f8083c62a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-roberta_qa_finetuned_state_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English RobertaForQuestionAnswering Cased model (from skandaonsolve) +author: John Snow Labs +name: roberta_qa_finetuned_state +date: 2024-09-24 +tags: [en, open_source, roberta, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `roberta-finetuned-state` is a English model originally trained by `skandaonsolve`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_state_en_5.5.0_3.0_1727210992386.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_finetuned_state_en_5.5.0_3.0_1727210992386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +Document_Assembler = MultiDocumentAssembler()\ + .setInputCols(["question", "context"])\ + .setOutputCols(["document_question", "document_context"]) + +Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_state","en")\ + .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 = RoBertaForQuestionAnswering.pretrained("roberta_qa_finetuned_state","en") + .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) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_finetuned_state| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.8 MB| + +## References + +References + +- https://huggingface.co/skandaonsolve/roberta-finetuned-state \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-roberta_qa_quales_iberlef_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-roberta_qa_quales_iberlef_pipeline_en.md new file mode 100644 index 00000000000000..667b4ab7493bf2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-roberta_qa_quales_iberlef_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_qa_quales_iberlef_pipeline pipeline RoBertaForQuestionAnswering from stevemobs +author: John Snow Labs +name: roberta_qa_quales_iberlef_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_qa_quales_iberlef_pipeline` is a English model originally trained by stevemobs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_qa_quales_iberlef_pipeline_en_5.5.0_3.0_1727210919809.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_qa_quales_iberlef_pipeline_en_5.5.0_3.0_1727210919809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_qa_quales_iberlef_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_qa_quales_iberlef_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_qa_quales_iberlef_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/stevemobs/quales-iberlef + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-securebert_en.md b/docs/_posts/ahmedlone127/2024-09-24-securebert_en.md new file mode 100644 index 00000000000000..5966cea4dee2b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-securebert_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English securebert RoBertaForSequenceClassification from ltkw98 +author: John Snow Labs +name: securebert +date: 2024-09-24 +tags: [roberta, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert` is a English model originally trained by ltkw98. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_en_5.5.0_3.0_1727216321312.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_en_5.5.0_3.0_1727216321312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = RoBertaForSequenceClassification.pretrained("securebert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = RoBertaForSequenceClassification.pretrained("securebert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|securebert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[roberta]| +|Language:|en| +|Size:|466.1 MB| + +## References + +References + +https://huggingface.co/ltkw98/SecureBert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline_en.md new file mode 100644 index 00000000000000..ca5c5690dc38a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline pipeline BertSentenceEmbeddings from betteib +author: John Snow Labs +name: sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline` is a English model originally trained by betteib. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline_en_5.5.0_3.0_1727202366871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline_en_5.5.0_3.0_1727202366871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_arabert_finetuned_mdeberta_tswana_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|505.1 MB| + +## References + +https://huggingface.co/betteib/bert-base-arabert-finetuned-mdeberta-tn + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-sent_turkish_mini_bert_uncased_tr.md b/docs/_posts/ahmedlone127/2024-09-24-sent_turkish_mini_bert_uncased_tr.md new file mode 100644 index 00000000000000..ab699c06c276b9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-sent_turkish_mini_bert_uncased_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish sent_turkish_mini_bert_uncased BertSentenceEmbeddings from ytu-ce-cosmos +author: John Snow Labs +name: sent_turkish_mini_bert_uncased +date: 2024-09-24 +tags: [tr, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_turkish_mini_bert_uncased` is a Turkish model originally trained by ytu-ce-cosmos. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_turkish_mini_bert_uncased_tr_5.5.0_3.0_1727202574857.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_turkish_mini_bert_uncased_tr_5.5.0_3.0_1727202574857.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_turkish_mini_bert_uncased","tr") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_turkish_mini_bert_uncased","tr") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_turkish_mini_bert_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|tr| +|Size:|43.3 MB| + +## References + +https://huggingface.co/ytu-ce-cosmos/turkish-mini-bert-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-squeezebert_uncased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-09-24-squeezebert_uncased_finetuned_squad_en.md new file mode 100644 index 00000000000000..6a47730da5b8e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-squeezebert_uncased_finetuned_squad_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English squeezebert_uncased_finetuned_squad BertForQuestionAnswering from SupriyaArun +author: John Snow Labs +name: squeezebert_uncased_finetuned_squad +date: 2024-09-24 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +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.`squeezebert_uncased_finetuned_squad` is a English model originally trained by SupriyaArun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/squeezebert_uncased_finetuned_squad_en_5.5.0_3.0_1727206782723.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/squeezebert_uncased_finetuned_squad_en_5.5.0_3.0_1727206782723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("squeezebert_uncased_finetuned_squad","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("squeezebert_uncased_finetuned_squad", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|squeezebert_uncased_finetuned_squad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|187.4 MB| + +## References + +https://huggingface.co/SupriyaArun/squeezebert-uncased-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-test_pipeline_en.md new file mode 100644 index 00000000000000..43501309146ca9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-test_pipeline_en.md @@ -0,0 +1,72 @@ +--- +layout: model +title: English test_pipeline pipeline RoBertaForQuestionAnswering from Nadav +author: John Snow Labs +name: test_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_pipeline` is a English model originally trained by Nadav. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_pipeline_en_5.5.0_3.0_1727156765054.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_pipeline_en_5.5.0_3.0_1727156765054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("test_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("test_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|877.1 MB| + +## References + +References + +https://huggingface.co/Nadav/test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-tmp_trainer_parth49_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-tmp_trainer_parth49_pipeline_en.md new file mode 100644 index 00000000000000..8dff8585de5933 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-tmp_trainer_parth49_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tmp_trainer_parth49_pipeline pipeline DistilBertForSequenceClassification from Parth49 +author: John Snow Labs +name: tmp_trainer_parth49_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tmp_trainer_parth49_pipeline` is a English model originally trained by Parth49. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tmp_trainer_parth49_pipeline_en_5.5.0_3.0_1727154783598.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tmp_trainer_parth49_pipeline_en_5.5.0_3.0_1727154783598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tmp_trainer_parth49_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tmp_trainer_parth49_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tmp_trainer_parth49_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|249.5 MB| + +## References + +https://huggingface.co/Parth49/tmp_trainer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-tuning_lr_0_1_wd_0_01_epochs_1_en.md b/docs/_posts/ahmedlone127/2024-09-24-tuning_lr_0_1_wd_0_01_epochs_1_en.md new file mode 100644 index 00000000000000..01809aa79dc423 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-tuning_lr_0_1_wd_0_01_epochs_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tuning_lr_0_1_wd_0_01_epochs_1 DistilBertForSequenceClassification from ash-akjp-ga +author: John Snow Labs +name: tuning_lr_0_1_wd_0_01_epochs_1 +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, distilbert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tuning_lr_0_1_wd_0_01_epochs_1` is a English model originally trained by ash-akjp-ga. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tuning_lr_0_1_wd_0_01_epochs_1_en_5.5.0_3.0_1727164656924.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tuning_lr_0_1_wd_0_01_epochs_1_en_5.5.0_3.0_1727164656924.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 = DistilBertForSequenceClassification.pretrained("tuning_lr_0_1_wd_0_01_epochs_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = DistilBertForSequenceClassification.pretrained("tuning_lr_0_1_wd_0_01_epochs_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tuning_lr_0_1_wd_0_01_epochs_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|251.0 MB| + +## References + +https://huggingface.co/ash-akjp-ga/tuning_lr_0.1_wd_0.01_epochs_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline_en.md new file mode 100644 index 00000000000000..8a072c3c13f096 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline pipeline XlmRoBertaForTokenClassification from kenhoffman +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline` is a English model originally trained by kenhoffman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline_en_5.5.0_3.0_1727160437812.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline_en_5.5.0_3.0_1727160437812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_english_kenhoffman_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|826.4 MB| + +## References + +https://huggingface.co/kenhoffman/xlm-roberta-base-finetuned-panx-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_english_skr1125_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_english_skr1125_pipeline_en.md new file mode 100644 index 00000000000000..386874f5d68dd0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_english_skr1125_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_english_skr1125_pipeline pipeline XlmRoBertaForTokenClassification from skr1125 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_english_skr1125_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_english_skr1125_pipeline` is a English model originally trained by skr1125. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_skr1125_pipeline_en_5.5.0_3.0_1727180242770.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_english_skr1125_pipeline_en_5.5.0_3.0_1727180242770.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_skr1125_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_english_skr1125_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_english_skr1125_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|826.4 MB| + +## References + +https://huggingface.co/skr1125/xlm-roberta-base-finetuned-panx-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline_en.md new file mode 100644 index 00000000000000..62fccdaf254467 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline pipeline XlmRoBertaForTokenClassification from LaurentiuStancioiu +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline +date: 2024-09-24 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline` is a English model originally trained by LaurentiuStancioiu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline_en_5.5.0_3.0_1727214890249.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline_en_5.5.0_3.0_1727214890249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_laurentiustancioiu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/LaurentiuStancioiu/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train_en.md b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train_en.md new file mode 100644 index 00000000000000..098ff9ef114c9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train XlmRoBertaForSequenceClassification from shanhy +author: John Snow Labs +name: xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train` is a English model originally trained by shanhy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train_en_5.5.0_3.0_1727156017474.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train_en_5.5.0_3.0_1727156017474.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 = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_lr0_001_seed42_kinyarwanda_hau_eng_train| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|827.8 MB| + +## References + +https://huggingface.co/shanhy/xlm-roberta-base_lr0.001_seed42_kin-hau-eng_train \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_vietnam_aug_swap_en.md b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_vietnam_aug_swap_en.md new file mode 100644 index 00000000000000..06ba2b02c6ff82 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_base_vietnam_aug_swap_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_vietnam_aug_swap XlmRoBertaForSequenceClassification from ThuyNT03 +author: John Snow Labs +name: xlm_roberta_base_vietnam_aug_swap +date: 2024-09-24 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_vietnam_aug_swap` is a English model originally trained by ThuyNT03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vietnam_aug_swap_en_5.5.0_3.0_1727152630834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_vietnam_aug_swap_en_5.5.0_3.0_1727152630834.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 = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_vietnam_aug_swap","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_vietnam_aug_swap", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_vietnam_aug_swap| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|794.3 MB| + +## References + +https://huggingface.co/ThuyNT03/xlm-roberta-base-VietNam-aug_swap \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline_fr.md new file mode 100644 index 00000000000000..8d62efb192b68b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-24-xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline_fr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: French xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline pipeline XlmRoBertaForSequenceClassification from waboucay +author: John Snow Labs +name: xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline +date: 2024-09-24 +tags: [fr, open_source, pipeline, onnx] +task: Text Classification +language: fr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline` is a French model originally trained by waboucay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline_fr_5.5.0_3.0_1727170546681.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline_fr_5.5.0_3.0_1727170546681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_longformer_base_4096_repnum_wl_rua_wl_3_classes_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|1.1 GB| + +## References + +https://huggingface.co/waboucay/xlm-roberta-longformer-base-4096-repnum_wl-rua_wl_3_classes + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-0329files_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-25-0329files_pipeline_zh.md new file mode 100644 index 00000000000000..2004ea8726d598 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-0329files_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese 0329files_pipeline pipeline BertForTokenClassification from sothisai1 +author: John Snow Labs +name: 0329files_pipeline +date: 2024-09-25 +tags: [zh, open_source, pipeline, onnx] +task: Named Entity Recognition +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`0329files_pipeline` is a Chinese model originally trained by sothisai1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/0329files_pipeline_zh_5.5.0_3.0_1727284153866.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/0329files_pipeline_zh_5.5.0_3.0_1727284153866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("0329files_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("0329files_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|0329files_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|406.1 MB| + +## References + +https://huggingface.co/sothisai1/0329files + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-aak_bert_base_cased_cpc_ricardo_talavera_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-aak_bert_base_cased_cpc_ricardo_talavera_pipeline_en.md new file mode 100644 index 00000000000000..5d22f4e5858194 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-aak_bert_base_cased_cpc_ricardo_talavera_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English aak_bert_base_cased_cpc_ricardo_talavera_pipeline pipeline BertForSequenceClassification from nishan007 +author: John Snow Labs +name: aak_bert_base_cased_cpc_ricardo_talavera_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aak_bert_base_cased_cpc_ricardo_talavera_pipeline` is a English model originally trained by nishan007. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aak_bert_base_cased_cpc_ricardo_talavera_pipeline_en_5.5.0_3.0_1727286379909.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aak_bert_base_cased_cpc_ricardo_talavera_pipeline_en_5.5.0_3.0_1727286379909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("aak_bert_base_cased_cpc_ricardo_talavera_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("aak_bert_base_cased_cpc_ricardo_talavera_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aak_bert_base_cased_cpc_ricardo_talavera_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/nishan007/aak-bert-base-cased-cpc-ricardo-talavera + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-ad_kd_bert_base_uncased_mrpc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-ad_kd_bert_base_uncased_mrpc_pipeline_en.md new file mode 100644 index 00000000000000..447f7dcc474391 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-ad_kd_bert_base_uncased_mrpc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ad_kd_bert_base_uncased_mrpc_pipeline pipeline BertForSequenceClassification from Brucewsy +author: John Snow Labs +name: ad_kd_bert_base_uncased_mrpc_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ad_kd_bert_base_uncased_mrpc_pipeline` is a English model originally trained by Brucewsy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ad_kd_bert_base_uncased_mrpc_pipeline_en_5.5.0_3.0_1727285834496.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ad_kd_bert_base_uncased_mrpc_pipeline_en_5.5.0_3.0_1727285834496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ad_kd_bert_base_uncased_mrpc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ad_kd_bert_base_uncased_mrpc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ad_kd_bert_base_uncased_mrpc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Brucewsy/AD-KD_bert_base_uncased_mrpc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-adrv2024_markadamsmsba24_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-adrv2024_markadamsmsba24_pipeline_en.md new file mode 100644 index 00000000000000..9254944db59e49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-adrv2024_markadamsmsba24_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English adrv2024_markadamsmsba24_pipeline pipeline BertForSequenceClassification from MarkAdamsMSBA24 +author: John Snow Labs +name: adrv2024_markadamsmsba24_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adrv2024_markadamsmsba24_pipeline` is a English model originally trained by MarkAdamsMSBA24. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adrv2024_markadamsmsba24_pipeline_en_5.5.0_3.0_1727267326953.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adrv2024_markadamsmsba24_pipeline_en_5.5.0_3.0_1727267326953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("adrv2024_markadamsmsba24_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("adrv2024_markadamsmsba24_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|adrv2024_markadamsmsba24_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MarkAdamsMSBA24/ADRv2024 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa_en.md b/docs/_posts/ahmedlone127/2024-09-25-aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa_en.md new file mode 100644 index 00000000000000..9788b81c7b987e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa BertForSequenceClassification from ys7yoo +author: John Snow Labs +name: aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa` is a English model originally trained by ys7yoo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa_en_5.5.0_3.0_1727287936356.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa_en_5.5.0_3.0_1727287936356.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("aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aes_bert_base_sp90_lr1e_05_wr1e_01_wd1e_02_ep15_elsa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/ys7yoo/aes_bert-base_sp90_lr1e-05_wr1e-01_wd1e-02_ep15_elsa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline_en.md new file mode 100644 index 00000000000000..15be0e24066ad6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline pipeline BertForSequenceClassification from kamel-usp +author: John Snow Labs +name: aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline` is a English model originally trained by kamel-usp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline_en_5.5.0_3.0_1727261720430.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline_en_5.5.0_3.0_1727261720430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aes_enem_models_sourcea_regression_from_bertimbau_large_c5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/kamel-usp/aes_enem_models-sourceA-regression-from-bertimbau-large-C5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-ag_news_9600_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-ag_news_9600_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..f944d404031a9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-ag_news_9600_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ag_news_9600_bert_base_uncased_pipeline pipeline BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: ag_news_9600_bert_base_uncased_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ag_news_9600_bert_base_uncased_pipeline` is a English model originally trained by Kyle1668. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ag_news_9600_bert_base_uncased_pipeline_en_5.5.0_3.0_1727300108997.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ag_news_9600_bert_base_uncased_pipeline_en_5.5.0_3.0_1727300108997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ag_news_9600_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ag_news_9600_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ag_news_9600_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/ag-news-9600-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-albert_base_chinese_ws_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-09-25-albert_base_chinese_ws_finetuned_ner_en.md new file mode 100644 index 00000000000000..9c4a380928e7a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-albert_base_chinese_ws_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_base_chinese_ws_finetuned_ner BertForTokenClassification from HYM +author: John Snow Labs +name: albert_base_chinese_ws_finetuned_ner +date: 2024-09-25 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_chinese_ws_finetuned_ner` is a English model originally trained by HYM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_chinese_ws_finetuned_ner_en_5.5.0_3.0_1727282644073.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_chinese_ws_finetuned_ner_en_5.5.0_3.0_1727282644073.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') + +tokenClassifier = BertForTokenClassification.pretrained("albert_base_chinese_ws_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("albert_base_chinese_ws_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_chinese_ws_finetuned_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|37.5 MB| + +## References + +https://huggingface.co/HYM/albert-base-chinese-ws-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-alberti128b128l_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-alberti128b128l_pipeline_en.md new file mode 100644 index 00000000000000..83113d57c377c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-alberti128b128l_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English alberti128b128l_pipeline pipeline BertForSequenceClassification from IvashinMaxim +author: John Snow Labs +name: alberti128b128l_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alberti128b128l_pipeline` is a English model originally trained by IvashinMaxim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alberti128b128l_pipeline_en_5.5.0_3.0_1727297619400.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alberti128b128l_pipeline_en_5.5.0_3.0_1727297619400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("alberti128b128l_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("alberti128b128l_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alberti128b128l_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|666.6 MB| + +## References + +https://huggingface.co/IvashinMaxim/alberti128b128l + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-autotrain_bertbase_imdb_1275748793_en.md b/docs/_posts/ahmedlone127/2024-09-25-autotrain_bertbase_imdb_1275748793_en.md new file mode 100644 index 00000000000000..2eabc0ca69599a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-autotrain_bertbase_imdb_1275748793_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autotrain_bertbase_imdb_1275748793 BertForSequenceClassification from sasha +author: John Snow Labs +name: autotrain_bertbase_imdb_1275748793 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_bertbase_imdb_1275748793` is a English model originally trained by sasha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748793_en_5.5.0_3.0_1727284857294.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748793_en_5.5.0_3.0_1727284857294.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("autotrain_bertbase_imdb_1275748793","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_bertbase_imdb_1275748793", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_bertbase_imdb_1275748793| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasha/autotrain-BERTBase-imdb-1275748793 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bengali_topic_all_doc_pipeline_bn.md b/docs/_posts/ahmedlone127/2024-09-25-bengali_topic_all_doc_pipeline_bn.md new file mode 100644 index 00000000000000..400db21512b189 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bengali_topic_all_doc_pipeline_bn.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Bengali bengali_topic_all_doc_pipeline pipeline BertForSequenceClassification from l3cube-pune +author: John Snow Labs +name: bengali_topic_all_doc_pipeline +date: 2024-09-25 +tags: [bn, open_source, pipeline, onnx] +task: Text Classification +language: bn +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bengali_topic_all_doc_pipeline` is a Bengali model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bengali_topic_all_doc_pipeline_bn_5.5.0_3.0_1727290616921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bengali_topic_all_doc_pipeline_bn_5.5.0_3.0_1727290616921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bengali_topic_all_doc_pipeline", lang = "bn") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bengali_topic_all_doc_pipeline", lang = "bn") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bengali_topic_all_doc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|bn| +|Size:|892.8 MB| + +## References + +https://huggingface.co/l3cube-pune/bengali-topic-all-doc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_amazon_product_classification_small_data_epoch_2_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_amazon_product_classification_small_data_epoch_2_en.md new file mode 100644 index 00000000000000..41635f19256473 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_amazon_product_classification_small_data_epoch_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_amazon_product_classification_small_data_epoch_2 BertForSequenceClassification from nthieu +author: John Snow Labs +name: bert_amazon_product_classification_small_data_epoch_2 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_amazon_product_classification_small_data_epoch_2` is a English model originally trained by nthieu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_amazon_product_classification_small_data_epoch_2_en_5.5.0_3.0_1727288352395.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_amazon_product_classification_small_data_epoch_2_en_5.5.0_3.0_1727288352395.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_amazon_product_classification_small_data_epoch_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_amazon_product_classification_small_data_epoch_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_amazon_product_classification_small_data_epoch_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/nthieu/bert-amazon-product-classification-small-data-epoch-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_bakuretso_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_bakuretso_pipeline_en.md new file mode 100644 index 00000000000000..f696960b4e8966 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_bakuretso_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_bakuretso_pipeline pipeline BertForSequenceClassification from Bakuretso +author: John Snow Labs +name: bert_base_banking77_pt2_bakuretso_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_bakuretso_pipeline` is a English model originally trained by Bakuretso. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_bakuretso_pipeline_en_5.5.0_3.0_1727266244742.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_bakuretso_pipeline_en_5.5.0_3.0_1727266244742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_bakuretso_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_bakuretso_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_bakuretso_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Bakuretso/bert-base-banking77-pt2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_jy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_jy_pipeline_en.md new file mode 100644 index 00000000000000..2f235bbc3f1808 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_jy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_jy_pipeline pipeline BertForSequenceClassification from SeoJeongYun +author: John Snow Labs +name: bert_base_banking77_pt2_jy_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_jy_pipeline` is a English model originally trained by SeoJeongYun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_jy_pipeline_en_5.5.0_3.0_1727304555836.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_jy_pipeline_en_5.5.0_3.0_1727304555836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_jy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_jy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_jy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/SeoJeongYun/bert-base-banking77-pt2-jy + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_lugrenl_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_lugrenl_en.md new file mode 100644 index 00000000000000..60c84bc01236fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_banking77_pt2_lugrenl_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pt2_lugrenl BertForSequenceClassification from lugrenl +author: John Snow Labs +name: bert_base_banking77_pt2_lugrenl +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_lugrenl` is a English model originally trained by lugrenl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_lugrenl_en_5.5.0_3.0_1727284866057.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_lugrenl_en_5.5.0_3.0_1727284866057.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_base_banking77_pt2_lugrenl","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_lugrenl", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_lugrenl| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/lugrenl/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_bookcorpus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_bookcorpus_pipeline_en.md new file mode 100644 index 00000000000000..0709581f713f27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_bookcorpus_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_bookcorpus_pipeline pipeline BertEmbeddings from AiresPucrs +author: John Snow Labs +name: bert_base_bookcorpus_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_bookcorpus_pipeline` is a English model originally trained by AiresPucrs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_bookcorpus_pipeline_en_5.5.0_3.0_1727240922579.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_bookcorpus_pipeline_en_5.5.0_3.0_1727240922579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_bookcorpus_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_bookcorpus_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_bookcorpus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.3 MB| + +## References + +https://huggingface.co/AiresPucrs/bert-base-bookcorpus + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_buddhist_sanskrit_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_buddhist_sanskrit_pipeline_en.md new file mode 100644 index 00000000000000..aca67b33c655fa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_buddhist_sanskrit_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_buddhist_sanskrit_pipeline pipeline BertEmbeddings from Matej +author: John Snow Labs +name: bert_base_buddhist_sanskrit_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_buddhist_sanskrit_pipeline` is a English model originally trained by Matej. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_buddhist_sanskrit_pipeline_en_5.5.0_3.0_1727255019993.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_buddhist_sanskrit_pipeline_en_5.5.0_3.0_1727255019993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_buddhist_sanskrit_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_buddhist_sanskrit_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_buddhist_sanskrit_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/Matej/bert-base-buddhist-sanskrit + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_case_ner_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_case_ner_en.md new file mode 100644 index 00000000000000..71ef88ab1c6450 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_case_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_case_ner BertForTokenClassification from raulgdp +author: John Snow Labs +name: bert_base_case_ner +date: 2024-09-25 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_case_ner` is a English model originally trained by raulgdp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_case_ner_en_5.5.0_3.0_1727280237489.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_case_ner_en_5.5.0_3.0_1727280237489.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_case_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_case_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_case_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/raulgdp/bert-base-case-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ft5_3ep_s42_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ft5_3ep_s42_pipeline_en.md new file mode 100644 index 00000000000000..a21f5f5d00e62c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ft5_3ep_s42_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_ft5_3ep_s42_pipeline pipeline BertForSequenceClassification from AbhishekkV19 +author: John Snow Labs +name: bert_base_cased_ft5_3ep_s42_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_ft5_3ep_s42_pipeline` is a English model originally trained by AbhishekkV19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft5_3ep_s42_pipeline_en_5.5.0_3.0_1727285710610.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft5_3ep_s42_pipeline_en_5.5.0_3.0_1727285710610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_ft5_3ep_s42_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_ft5_3ep_s42_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_ft5_3ep_s42_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/AbhishekkV19/bert-base-cased-ft5-3ep-s42 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ft6_3ep_s42_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ft6_3ep_s42_2_pipeline_en.md new file mode 100644 index 00000000000000..3f20f162bf0c7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ft6_3ep_s42_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_ft6_3ep_s42_2_pipeline pipeline BertForSequenceClassification from AbhishekkV19 +author: John Snow Labs +name: bert_base_cased_ft6_3ep_s42_2_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_ft6_3ep_s42_2_pipeline` is a English model originally trained by AbhishekkV19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft6_3ep_s42_2_pipeline_en_5.5.0_3.0_1727290287834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft6_3ep_s42_2_pipeline_en_5.5.0_3.0_1727290287834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_ft6_3ep_s42_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_ft6_3ep_s42_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_ft6_3ep_s42_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/AbhishekkV19/bert-base-cased-ft6-3ep-s42-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_mnli_model7_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_mnli_model7_en.md new file mode 100644 index 00000000000000..5bf56e00fbe92b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_mnli_model7_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_mnli_model7 BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_mnli_model7 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_model7` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_model7_en_5.5.0_3.0_1727289209219.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_model7_en_5.5.0_3.0_1727289209219.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_base_cased_mnli_model7","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_mnli_model7", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_mnli_model7| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-mnli-model7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_mnli_model7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_mnli_model7_pipeline_en.md new file mode 100644 index 00000000000000..9d1be310d62aba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_mnli_model7_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_mnli_model7_pipeline pipeline BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_mnli_model7_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_mnli_model7_pipeline` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_model7_pipeline_en_5.5.0_3.0_1727289230603.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_model7_pipeline_en_5.5.0_3.0_1727289230603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_mnli_model7_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_mnli_model7_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_mnli_model7_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-mnli-model7 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ner_chuvash_med_ft_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ner_chuvash_med_ft_pipeline_en.md new file mode 100644 index 00000000000000..d6ef768757ff4c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_ner_chuvash_med_ft_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_ner_chuvash_med_ft_pipeline pipeline BertForTokenClassification from jhonparra18 +author: John Snow Labs +name: bert_base_cased_ner_chuvash_med_ft_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_ner_chuvash_med_ft_pipeline` is a English model originally trained by jhonparra18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_ner_chuvash_med_ft_pipeline_en_5.5.0_3.0_1727271120727.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_ner_chuvash_med_ft_pipeline_en_5.5.0_3.0_1727271120727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_ner_chuvash_med_ft_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_ner_chuvash_med_ft_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_ner_chuvash_med_ft_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/jhonparra18/bert-base-cased-ner_cv-med-ft + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_textcls_rheology_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_textcls_rheology_en.md new file mode 100644 index 00000000000000..2467cfe1f1fc6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_cased_textcls_rheology_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_textcls_rheology BertForSequenceClassification from jonas-luehrs +author: John Snow Labs +name: bert_base_cased_textcls_rheology +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_textcls_rheology` is a English model originally trained by jonas-luehrs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_textcls_rheology_en_5.5.0_3.0_1727272952057.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_textcls_rheology_en_5.5.0_3.0_1727272952057.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_base_cased_textcls_rheology","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_textcls_rheology", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_textcls_rheology| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jonas-luehrs/bert-base-cased-textCLS-RHEOLOGY \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest_en.md new file mode 100644 index 00000000000000..62b48707ea9a31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest BertForSequenceClassification from Wiebke +author: John Snow Labs +name: bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_casedepoch3_sexist_baseline_with_reddit_and_gabfortest` is a English model originally trained by Wiebke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest_en_5.5.0_3.0_1727284504508.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest_en_5.5.0_3.0_1727284504508.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_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_casedepoch3_sexist_baseline_with_reddit_and_gabfortest| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Wiebke/bert-base-casedepoch3_sexist_baseline_with_reddit_and_gabfortest \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline_en.md new file mode 100644 index 00000000000000..763858d00ec1f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline_en_5.5.0_3.0_1727285709483.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline_en_5.5.0_3.0_1727285709483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_v4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-v4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline_en.md new file mode 100644 index 00000000000000..0d6ca068e600fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline_en_5.5.0_3.0_1727276373121.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline_en_5.5.0_3.0_1727276373121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_transition_physical_risk_prediction_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-transition-physical-risk-prediction-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline_zh.md new file mode 100644 index 00000000000000..e6946ceb90a051 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline +date: 2024-09-25 +tags: [zh, open_source, pipeline, onnx] +task: Text Classification +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline` is a Chinese model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline_zh_5.5.0_3.0_1727286017991.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline_zh_5.5.0_3.0_1727286017991.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuning_financial_news_sentiment_test1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-finetuning-financial-news-sentiment-test1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_german_cased_archaeo_ner_de.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_german_cased_archaeo_ner_de.md new file mode 100644 index 00000000000000..3096cbb9d6a012 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_german_cased_archaeo_ner_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German bert_base_german_cased_archaeo_ner BertForTokenClassification from alexbrandsen +author: John Snow Labs +name: bert_base_german_cased_archaeo_ner +date: 2024-09-25 +tags: [de, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_archaeo_ner` is a German model originally trained by alexbrandsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_archaeo_ner_de_5.5.0_3.0_1727246612686.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_archaeo_ner_de_5.5.0_3.0_1727246612686.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_german_cased_archaeo_ner","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_german_cased_archaeo_ner", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_german_cased_archaeo_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|406.9 MB| + +## References + +https://huggingface.co/alexbrandsen/bert-base-german-cased-archaeo-NER \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2_en.md new file mode 100644 index 00000000000000..e0cff4e3bbe6f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2 BertForTokenClassification from tbosse +author: John Snow Labs +name: bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2 +date: 2024-09-25 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2` is a English model originally trained by tbosse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2_en_5.5.0_3.0_1727280896318.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2_en_5.5.0_3.0_1727280896318.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_german_cased_noisy_pretrain_fine_tuned_v1_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/tbosse/bert-base-german-cased-noisy-pretrain-fine-tuned_v1.2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_cased_vtoc_1_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_cased_vtoc_1_pipeline_xx.md new file mode 100644 index 00000000000000..527849a989af02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_cased_vtoc_1_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_vtoc_1_pipeline pipeline BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_vtoc_1_pipeline +date: 2024-09-25 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_vtoc_1_pipeline` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_vtoc_1_pipeline_xx_5.5.0_3.0_1727289139379.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_vtoc_1_pipeline_xx_5.5.0_3.0_1727289139379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_vtoc_1_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_vtoc_1_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_vtoc_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-vtoc-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_cased_wnli_1_xx.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_cased_wnli_1_xx.md new file mode 100644 index 00000000000000..2cc8ccdfe79425 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_cased_wnli_1_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_wnli_1 BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_wnli_1 +date: 2024-09-25 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_wnli_1` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_wnli_1_xx_5.5.0_3.0_1727284991226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_wnli_1_xx_5.5.0_3.0_1727284991226.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_base_multilingual_cased_wnli_1","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_wnli_1", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_wnli_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-wnli-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_akazi_xx.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_akazi_xx.md new file mode 100644 index 00000000000000..04c67dd2d1219d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_akazi_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_akazi BertForSequenceClassification from Akazi +author: John Snow Labs +name: bert_base_multilingual_uncased_akazi +date: 2024-09-25 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_akazi` is a Multilingual model originally trained by Akazi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_akazi_xx_5.5.0_3.0_1727284528288.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_akazi_xx_5.5.0_3.0_1727284528288.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_base_multilingual_uncased_akazi","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_akazi", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_akazi| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/Akazi/bert-base-multilingual-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_sentiment_eternaut_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_sentiment_eternaut_pipeline_xx.md new file mode 100644 index 00000000000000..6ba44e39036b9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_sentiment_eternaut_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_sentiment_eternaut_pipeline pipeline BertForSequenceClassification from eternaut +author: John Snow Labs +name: bert_base_multilingual_uncased_sentiment_eternaut_pipeline +date: 2024-09-25 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_sentiment_eternaut_pipeline` is a Multilingual model originally trained by eternaut. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_sentiment_eternaut_pipeline_xx_5.5.0_3.0_1727290331563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_sentiment_eternaut_pipeline_xx_5.5.0_3.0_1727290331563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_uncased_sentiment_eternaut_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_uncased_sentiment_eternaut_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_sentiment_eternaut_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/eternaut/bert-base-multilingual-uncased-sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_vaxxstance_spanish_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_vaxxstance_spanish_pipeline_xx.md new file mode 100644 index 00000000000000..d2caa83bc39ed2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_multilingual_uncased_vaxxstance_spanish_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_vaxxstance_spanish_pipeline pipeline BertForSequenceClassification from nouman-10 +author: John Snow Labs +name: bert_base_multilingual_uncased_vaxxstance_spanish_pipeline +date: 2024-09-25 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_vaxxstance_spanish_pipeline` is a Multilingual model originally trained by nouman-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_vaxxstance_spanish_pipeline_xx_5.5.0_3.0_1727277493129.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_vaxxstance_spanish_pipeline_xx_5.5.0_3.0_1727277493129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_uncased_vaxxstance_spanish_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_uncased_vaxxstance_spanish_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_vaxxstance_spanish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/nouman-10/bert-base-multilingual-uncased_vaxxstance_spanish + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_portuguese_fine_tuned_mrpc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_portuguese_fine_tuned_mrpc_pipeline_en.md new file mode 100644 index 00000000000000..e9ed079350ca63 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_portuguese_fine_tuned_mrpc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_portuguese_fine_tuned_mrpc_pipeline pipeline BertForSequenceClassification from erickrribeiro +author: John Snow Labs +name: bert_base_portuguese_fine_tuned_mrpc_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_portuguese_fine_tuned_mrpc_pipeline` is a English model originally trained by erickrribeiro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_fine_tuned_mrpc_pipeline_en_5.5.0_3.0_1727273610123.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_fine_tuned_mrpc_pipeline_en_5.5.0_3.0_1727273610123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_portuguese_fine_tuned_mrpc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_portuguese_fine_tuned_mrpc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_portuguese_fine_tuned_mrpc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/erickrribeiro/bert-base-portuguese-fine-tuned-mrpc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_sayula_popoluca_theseus_bulgarian_pipeline_bg.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_sayula_popoluca_theseus_bulgarian_pipeline_bg.md new file mode 100644 index 00000000000000..97da56d935f543 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_sayula_popoluca_theseus_bulgarian_pipeline_bg.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Bulgarian bert_base_sayula_popoluca_theseus_bulgarian_pipeline pipeline BertForTokenClassification from rmihaylov +author: John Snow Labs +name: bert_base_sayula_popoluca_theseus_bulgarian_pipeline +date: 2024-09-25 +tags: [bg, open_source, pipeline, onnx] +task: Named Entity Recognition +language: bg +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_sayula_popoluca_theseus_bulgarian_pipeline` is a Bulgarian model originally trained by rmihaylov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_sayula_popoluca_theseus_bulgarian_pipeline_bg_5.5.0_3.0_1727274986511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_sayula_popoluca_theseus_bulgarian_pipeline_bg_5.5.0_3.0_1727274986511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_sayula_popoluca_theseus_bulgarian_pipeline", lang = "bg") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_sayula_popoluca_theseus_bulgarian_pipeline", lang = "bg") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_sayula_popoluca_theseus_bulgarian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|bg| +|Size:|505.5 MB| + +## References + +https://huggingface.co/rmihaylov/bert-base-pos-theseus-bg + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_boot_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_boot_en.md new file mode 100644 index 00000000000000..98c86c49c10aa8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_boot_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_temp_classifier_boot BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_temp_classifier_boot +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_temp_classifier_boot` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_temp_classifier_boot_en_5.5.0_3.0_1727288170613.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_temp_classifier_boot_en_5.5.0_3.0_1727288170613.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_base_temp_classifier_boot","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_temp_classifier_boot", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_temp_classifier_boot| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/research-dump/bert_base_temp_classifier_boot \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_en.md new file mode 100644 index 00000000000000..5e18498327d414 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_temp_classifier BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_temp_classifier +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_temp_classifier` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_temp_classifier_en_5.5.0_3.0_1727284973238.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_temp_classifier_en_5.5.0_3.0_1727284973238.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_base_temp_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_temp_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_temp_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/research-dump/bert_base_temp_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_pipeline_en.md new file mode 100644 index 00000000000000..5a0a60e2b913a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_temp_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_temp_classifier_pipeline pipeline BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_temp_classifier_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_temp_classifier_pipeline` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_temp_classifier_pipeline_en_5.5.0_3.0_1727284994745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_temp_classifier_pipeline_en_5.5.0_3.0_1727284994745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_temp_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_temp_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_temp_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/research-dump/bert_base_temp_classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_data_influence_model_lambada_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_data_influence_model_lambada_en.md new file mode 100644 index 00000000000000..747cf4c271ef71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_data_influence_model_lambada_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_data_influence_model_lambada BertForSequenceClassification from yuzc19 +author: John Snow Labs +name: bert_base_uncased_data_influence_model_lambada +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_data_influence_model_lambada` is a English model originally trained by yuzc19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_data_influence_model_lambada_en_5.5.0_3.0_1727263775126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_data_influence_model_lambada_en_5.5.0_3.0_1727263775126.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_base_uncased_data_influence_model_lambada","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_data_influence_model_lambada", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_data_influence_model_lambada| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yuzc19/bert-base-uncased-data-influence-model-lambada \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_pysentimiento_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_pysentimiento_pipeline_en.md new file mode 100644 index 00000000000000..677d33d9d18ecb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_pysentimiento_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_emotion_pysentimiento_pipeline pipeline BertForSequenceClassification from pysentimiento +author: John Snow Labs +name: bert_base_uncased_emotion_pysentimiento_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_emotion_pysentimiento_pipeline` is a English model originally trained by pysentimiento. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_pysentimiento_pipeline_en_5.5.0_3.0_1727306399043.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_pysentimiento_pipeline_en_5.5.0_3.0_1727306399043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_emotion_pysentimiento_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_emotion_pysentimiento_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_pysentimiento_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/pysentimiento/bert-base-uncased-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_ricocheh_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_ricocheh_en.md new file mode 100644 index 00000000000000..59fc88bdd48254 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_ricocheh_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_emotion_ricocheh BertForSequenceClassification from RicoCHEH +author: John Snow Labs +name: bert_base_uncased_emotion_ricocheh +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ricocheh` is a English model originally trained by RicoCHEH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_ricocheh_en_5.5.0_3.0_1727308420367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_ricocheh_en_5.5.0_3.0_1727308420367.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_base_uncased_emotion_ricocheh","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_emotion_ricocheh", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_ricocheh| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/RicoCHEH/bert-base-uncased-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_v1_pipeline_en.md new file mode 100644 index 00000000000000..52127d30f717eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_emotion_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_emotion_v1_pipeline pipeline BertForSequenceClassification from Cesar42 +author: John Snow Labs +name: bert_base_uncased_emotion_v1_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_emotion_v1_pipeline` is a English model originally trained by Cesar42. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_v1_pipeline_en_5.5.0_3.0_1727279812047.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_v1_pipeline_en_5.5.0_3.0_1727279812047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_emotion_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_emotion_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Cesar42/bert-base-uncased-emotion_v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_chemprot_corpus_re_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_chemprot_corpus_re_pipeline_en.md new file mode 100644 index 00000000000000..058dff92b76fd0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_chemprot_corpus_re_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_chemprot_corpus_re_pipeline pipeline BertForSequenceClassification from maksim2000153 +author: John Snow Labs +name: bert_base_uncased_finetuned_chemprot_corpus_re_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_chemprot_corpus_re_pipeline` is a English model originally trained by maksim2000153. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_chemprot_corpus_re_pipeline_en_5.5.0_3.0_1727269463851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_chemprot_corpus_re_pipeline_en_5.5.0_3.0_1727269463851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_chemprot_corpus_re_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_chemprot_corpus_re_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_chemprot_corpus_re_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/maksim2000153/bert-base-uncased-finetuned-ChemProt-corpus-re + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_cola_senihylmz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_cola_senihylmz_pipeline_en.md new file mode 100644 index 00000000000000..5405485476cd9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_cola_senihylmz_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_senihylmz_pipeline pipeline BertForSequenceClassification from senihylmz +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_senihylmz_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_senihylmz_pipeline` is a English model originally trained by senihylmz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_senihylmz_pipeline_en_5.5.0_3.0_1727285397305.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_senihylmz_pipeline_en_5.5.0_3.0_1727285397305.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_senihylmz_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_senihylmz_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_senihylmz_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/senihylmz/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_filtered_0602_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_filtered_0602_pipeline_en.md new file mode 100644 index 00000000000000..cfde0b567bba4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_filtered_0602_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_filtered_0602_pipeline pipeline BertForSequenceClassification from YeRyeongLee +author: John Snow Labs +name: bert_base_uncased_finetuned_filtered_0602_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_filtered_0602_pipeline` is a English model originally trained by YeRyeongLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_filtered_0602_pipeline_en_5.5.0_3.0_1727284715085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_filtered_0602_pipeline_en_5.5.0_3.0_1727284715085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_filtered_0602_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_filtered_0602_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_filtered_0602_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/YeRyeongLee/bert-base-uncased-finetuned-filtered-0602 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar_en.md new file mode 100644 index 00000000000000..fb6c81c5febbe2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar BertForSequenceClassification from SandyDelMar +author: John Snow Labs +name: bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_meia_analisisdesentimientos_sandydelmar` is a English model originally trained by SandyDelMar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar_en_5.5.0_3.0_1727291624453.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar_en_5.5.0_3.0_1727291624453.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_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_meia_analisisdesentimientos_sandydelmar| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/SandyDelMar/bert-base-uncased-finetuned-MeIA-AnalisisDeSentimientos \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_news_1929_1932_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_news_1929_1932_en.md new file mode 100644 index 00000000000000..afd65252454ced --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_news_1929_1932_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_news_1929_1932 BertEmbeddings from sally9805 +author: John Snow Labs +name: bert_base_uncased_finetuned_news_1929_1932 +date: 2024-09-25 +tags: [en, open_source, onnx, embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_news_1929_1932` is a English model originally trained by sally9805. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1929_1932_en_5.5.0_3.0_1727254923888.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_1929_1932_en_5.5.0_3.0_1727254923888.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") + +embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1929_1932","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("bert_base_uncased_finetuned_news_1929_1932","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_news_1929_1932| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/sally9805/bert-base-uncased-finetuned-news-1929-1932 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_sst2_minseok0809_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_sst2_minseok0809_en.md new file mode 100644 index 00000000000000..43cab657f5ab12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_sst2_minseok0809_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sst2_minseok0809 BertForSequenceClassification from minseok0809 +author: John Snow Labs +name: bert_base_uncased_finetuned_sst2_minseok0809 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sst2_minseok0809` is a English model originally trained by minseok0809. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_minseok0809_en_5.5.0_3.0_1727308690389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_minseok0809_en_5.5.0_3.0_1727308690389.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_base_uncased_finetuned_sst2_minseok0809","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sst2_minseok0809", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sst2_minseok0809| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/minseok0809/bert-base-uncased-finetuned-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_sst2_sst2_membership_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_sst2_sst2_membership_en.md new file mode 100644 index 00000000000000..d5c0ca92053175 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_sst2_sst2_membership_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sst2_sst2_membership BertForSequenceClassification from doyoungkim +author: John Snow Labs +name: bert_base_uncased_finetuned_sst2_sst2_membership +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sst2_sst2_membership` is a English model originally trained by doyoungkim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_sst2_membership_en_5.5.0_3.0_1727307003826.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_sst2_membership_en_5.5.0_3.0_1727307003826.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_base_uncased_finetuned_sst2_sst2_membership","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sst2_sst2_membership", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sst2_sst2_membership| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/doyoungkim/bert-base-uncased-finetuned-sst2-sst2-membership \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_toxic_comment_detection_ws23_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_toxic_comment_detection_ws23_en.md new file mode 100644 index 00000000000000..4c0ee7795f4f13 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_finetuned_toxic_comment_detection_ws23_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_toxic_comment_detection_ws23 BertForSequenceClassification from tillschwoerer +author: John Snow Labs +name: bert_base_uncased_finetuned_toxic_comment_detection_ws23 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_toxic_comment_detection_ws23` is a English model originally trained by tillschwoerer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_toxic_comment_detection_ws23_en_5.5.0_3.0_1727261077962.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_toxic_comment_detection_ws23_en_5.5.0_3.0_1727261077962.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_base_uncased_finetuned_toxic_comment_detection_ws23","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_toxic_comment_detection_ws23", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_toxic_comment_detection_ws23| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tillschwoerer/bert-base-uncased-finetuned-toxic-comment-detection-ws23 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_glue_cola_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_glue_cola_en.md new file mode 100644 index 00000000000000..6b733b8b084041 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_glue_cola_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_glue_cola BertForSequenceClassification from pmthangk09 +author: John Snow Labs +name: bert_base_uncased_glue_cola +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_glue_cola` is a English model originally trained by pmthangk09. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_glue_cola_en_5.5.0_3.0_1727266373862.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_glue_cola_en_5.5.0_3.0_1727266373862.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_base_uncased_glue_cola","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_glue_cola", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_glue_cola| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/pmthangk09/bert-base-uncased-glue-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline_en.md new file mode 100644 index 00000000000000..432b8e6b10ace0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline pipeline BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline` 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_1h2r_pipeline_en_5.5.0_3.0_1727285899269.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_1h2r_pipeline_en_5.5.0_3.0_1727285899269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_hoax_classifier_fulltext_1h2r_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/research-dump/bert-base-uncased_hoax_classifier_fulltext_1h2r + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_issues_128_anantonios9_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_issues_128_anantonios9_en.md new file mode 100644 index 00000000000000..63b50c67f7b265 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_issues_128_anantonios9_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_issues_128_anantonios9 BertEmbeddings from anantonios9 +author: John Snow Labs +name: bert_base_uncased_issues_128_anantonios9 +date: 2024-09-25 +tags: [en, open_source, onnx, embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_anantonios9` is a English model originally trained by anantonios9. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_anantonios9_en_5.5.0_3.0_1727255952838.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_anantonios9_en_5.5.0_3.0_1727255952838.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") + +embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_anantonios9","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = BertEmbeddings.pretrained("bert_base_uncased_issues_128_anantonios9","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_issues_128_anantonios9| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/anantonios9/bert-base-uncased-issues-128 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_issues_128_pensuke_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_issues_128_pensuke_pipeline_en.md new file mode 100644 index 00000000000000..4ab09c0ecb529f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_issues_128_pensuke_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_issues_128_pensuke_pipeline pipeline BertEmbeddings from pensuke +author: John Snow Labs +name: bert_base_uncased_issues_128_pensuke_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_issues_128_pensuke_pipeline` is a English model originally trained by pensuke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_pensuke_pipeline_en_5.5.0_3.0_1727258559128.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_issues_128_pensuke_pipeline_en_5.5.0_3.0_1727258559128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_issues_128_pensuke_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_issues_128_pensuke_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_issues_128_pensuke_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/pensuke/bert-base-uncased-issues-128 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline_en.md new file mode 100644 index 00000000000000..0a1cff3ca36306 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline pipeline BertForSequenceClassification from jonas-luehrs +author: John Snow Labs +name: bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline` is a English model originally trained by jonas-luehrs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline_en_5.5.0_3.0_1727263824222.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline_en_5.5.0_3.0_1727263824222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mlp_scirepeval_chemistry_large_textcls_rheology_20230913_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jonas-luehrs/bert-base-uncased-MLP-scirepeval-chemistry-LARGE-textCLS-RHEOLOGY-20230913-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline_en.md new file mode 100644 index 00000000000000..7923e61772e1ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline pipeline BertForSequenceClassification from prateeky2806 +author: John Snow Labs +name: bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline` is a English model originally trained by prateeky2806. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline_en_5.5.0_3.0_1727306230697.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline_en_5.5.0_3.0_1727306230697.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst2_epochs_2_lr_0_0001_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/prateeky2806/bert-base-uncased-sst2-epochs-2-lr-0.0001 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_toxicity_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_toxicity_pipeline_en.md new file mode 100644 index 00000000000000..3fa6002194e0b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_toxicity_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_toxicity_pipeline pipeline BertForSequenceClassification from mohsenfayyaz +author: John Snow Labs +name: bert_base_uncased_toxicity_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_toxicity_pipeline` is a English model originally trained by mohsenfayyaz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_toxicity_pipeline_en_5.5.0_3.0_1727269914260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_toxicity_pipeline_en_5.5.0_3.0_1727269914260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_toxicity_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_toxicity_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_toxicity_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mohsenfayyaz/bert-base-uncased-toxicity + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_yelp_reviews_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_yelp_reviews_en.md new file mode 100644 index 00000000000000..0c212a0d99dbcb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_base_uncased_yelp_reviews_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_yelp_reviews BertForSequenceClassification from rttl-ai +author: John Snow Labs +name: bert_base_uncased_yelp_reviews +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_yelp_reviews` is a English model originally trained by rttl-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_yelp_reviews_en_5.5.0_3.0_1727307428384.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_yelp_reviews_en_5.5.0_3.0_1727307428384.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_base_uncased_yelp_reviews","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_yelp_reviews", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_yelp_reviews| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.7 MB| + +## References + +https://huggingface.co/rttl-ai/bert-base-uncased-yelp-reviews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_classifier_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_classifier_tuned_pipeline_en.md new file mode 100644 index 00000000000000..c6f5dbcc083fcf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_classifier_tuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classifier_tuned_pipeline pipeline BertForSequenceClassification from omgavy +author: John Snow Labs +name: bert_classifier_tuned_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_tuned_pipeline` is a English model originally trained by omgavy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_tuned_pipeline_en_5.5.0_3.0_1727267563867.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_tuned_pipeline_en_5.5.0_3.0_1727267563867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_tuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_tuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_tuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/omgavy/bert-classifier-tuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_cn_finetuning_wangyuwei_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_cn_finetuning_wangyuwei_en.md new file mode 100644 index 00000000000000..62dfe005287de0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_cn_finetuning_wangyuwei_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_cn_finetuning_wangyuwei BertForSequenceClassification from wangyuwei +author: John Snow Labs +name: bert_cn_finetuning_wangyuwei +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_wangyuwei` is a English model originally trained by wangyuwei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_wangyuwei_en_5.5.0_3.0_1727288846193.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_wangyuwei_en_5.5.0_3.0_1727288846193.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_cn_finetuning_wangyuwei","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_wangyuwei", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetuning_wangyuwei| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/wangyuwei/bert_cn_finetuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_election2020_twitter_stance_biden_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_election2020_twitter_stance_biden_pipeline_en.md new file mode 100644 index 00000000000000..6ab7ce23882696 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_election2020_twitter_stance_biden_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_election2020_twitter_stance_biden_pipeline pipeline BertForSequenceClassification from kornosk +author: John Snow Labs +name: bert_election2020_twitter_stance_biden_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_election2020_twitter_stance_biden_pipeline` is a English model originally trained by kornosk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_election2020_twitter_stance_biden_pipeline_en_5.5.0_3.0_1727239486271.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_election2020_twitter_stance_biden_pipeline_en_5.5.0_3.0_1727239486271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_election2020_twitter_stance_biden_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_election2020_twitter_stance_biden_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_election2020_twitter_stance_biden_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.8 MB| + +## References + +https://huggingface.co/kornosk/bert-election2020-twitter-stance-biden + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_fakenews_binaryclassification_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_fakenews_binaryclassification_en.md new file mode 100644 index 00000000000000..2175496c62dd4c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_fakenews_binaryclassification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_fakenews_binaryclassification BertForSequenceClassification from Arjun24420 +author: John Snow Labs +name: bert_fakenews_binaryclassification +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_binaryclassification` is a English model originally trained by Arjun24420. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fakenews_binaryclassification_en_5.5.0_3.0_1727308693892.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fakenews_binaryclassification_en_5.5.0_3.0_1727308693892.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_fakenews_binaryclassification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fakenews_binaryclassification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fakenews_binaryclassification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Arjun24420/BERT-FakeNews-BinaryClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_fakenews_binaryclassification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_fakenews_binaryclassification_pipeline_en.md new file mode 100644 index 00000000000000..7e4c500156ae99 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_fakenews_binaryclassification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_fakenews_binaryclassification_pipeline pipeline BertForSequenceClassification from Arjun24420 +author: John Snow Labs +name: bert_fakenews_binaryclassification_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fakenews_binaryclassification_pipeline` is a English model originally trained by Arjun24420. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fakenews_binaryclassification_pipeline_en_5.5.0_3.0_1727308715946.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fakenews_binaryclassification_pipeline_en_5.5.0_3.0_1727308715946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_fakenews_binaryclassification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_fakenews_binaryclassification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fakenews_binaryclassification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Arjun24420/BERT-FakeNews-BinaryClassification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_fined_tuned_cola_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_fined_tuned_cola_pipeline_en.md new file mode 100644 index 00000000000000..8cad1a7751bb1d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_fined_tuned_cola_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_fined_tuned_cola_pipeline pipeline BertForSequenceClassification from Utshav +author: John Snow Labs +name: bert_fined_tuned_cola_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fined_tuned_cola_pipeline` is a English model originally trained by Utshav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fined_tuned_cola_pipeline_en_5.5.0_3.0_1727288363559.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fined_tuned_cola_pipeline_en_5.5.0_3.0_1727288363559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_fined_tuned_cola_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_fined_tuned_cola_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fined_tuned_cola_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Utshav/bert-fined-tuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_age_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_age_en.md new file mode 100644 index 00000000000000..8eeef1fd16443c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_age_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_age BertForSequenceClassification from Abderrahim2 +author: John Snow Labs +name: bert_finetuned_age +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_age` is a English model originally trained by Abderrahim2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_age_en_5.5.0_3.0_1727276367575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_age_en_5.5.0_3.0_1727276367575.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_finetuned_age","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_age", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_age| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.5 MB| + +## References + +https://huggingface.co/Abderrahim2/bert-finetuned-Age \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_c_requirementtd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_c_requirementtd_pipeline_en.md new file mode 100644 index 00000000000000..dc3203b138cd79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_c_requirementtd_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_c_requirementtd_pipeline pipeline BertForSequenceClassification from maimaiT +author: John Snow Labs +name: bert_finetuned_c_requirementtd_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_c_requirementtd_pipeline` is a English model originally trained by maimaiT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_c_requirementtd_pipeline_en_5.5.0_3.0_1727276374625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_c_requirementtd_pipeline_en_5.5.0_3.0_1727276374625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_c_requirementtd_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_c_requirementtd_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_c_requirementtd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/maimaiT/BERT_finetuned_C_RequirementTD + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_hausa_ner_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_hausa_ner_en.md new file mode 100644 index 00000000000000..b2b294286e8e96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_hausa_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_hausa_ner BertForTokenClassification from peteryushunli +author: John Snow Labs +name: bert_finetuned_hausa_ner +date: 2024-09-25 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_hausa_ner` is a English model originally trained by peteryushunli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_hausa_ner_en_5.5.0_3.0_1727260005562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_hausa_ner_en_5.5.0_3.0_1727260005562.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_hausa_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_hausa_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_hausa_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/peteryushunli/bert-finetuned-hausa_ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_ner_hydrochii_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_ner_hydrochii_pipeline_en.md new file mode 100644 index 00000000000000..83b4d5556294c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_finetuned_ner_hydrochii_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_hydrochii_pipeline pipeline BertForTokenClassification from hydrochii +author: John Snow Labs +name: bert_finetuned_ner_hydrochii_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_hydrochii_pipeline` is a English model originally trained by hydrochii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_hydrochii_pipeline_en_5.5.0_3.0_1727270756112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_hydrochii_pipeline_en_5.5.0_3.0_1727270756112.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_hydrochii_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_hydrochii_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_hydrochii_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/hydrochii/bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_finnish_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_finnish_sentiment_analysis_en.md new file mode 100644 index 00000000000000..be8e0bc8b82777 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_finnish_sentiment_analysis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finnish_sentiment_analysis BertForSequenceClassification from nisancoskun +author: John Snow Labs +name: bert_finnish_sentiment_analysis +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finnish_sentiment_analysis` is a English model originally trained by nisancoskun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finnish_sentiment_analysis_en_5.5.0_3.0_1727263524860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finnish_sentiment_analysis_en_5.5.0_3.0_1727263524860.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_finnish_sentiment_analysis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finnish_sentiment_analysis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finnish_sentiment_analysis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|466.9 MB| + +## References + +https://huggingface.co/nisancoskun/bert-finnish-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_large_book_genre_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_large_book_genre_classification_pipeline_en.md new file mode 100644 index 00000000000000..4f60354af37d16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_large_book_genre_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_book_genre_classification_pipeline pipeline BertForSequenceClassification from TenzinGayche +author: John Snow Labs +name: bert_large_book_genre_classification_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_book_genre_classification_pipeline` is a English model originally trained by TenzinGayche. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_book_genre_classification_pipeline_en_5.5.0_3.0_1727306638660.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_book_genre_classification_pipeline_en_5.5.0_3.0_1727306638660.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_book_genre_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_book_genre_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_book_genre_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/TenzinGayche/Bert-large-book-genre-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_large_ner_pii_062024_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_large_ner_pii_062024_pipeline_en.md new file mode 100644 index 00000000000000..6e4c7e9c21c4db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_large_ner_pii_062024_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_ner_pii_062024_pipeline pipeline BertForTokenClassification from vuminhtue +author: John Snow Labs +name: bert_large_ner_pii_062024_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_ner_pii_062024_pipeline` is a English model originally trained by vuminhtue. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_ner_pii_062024_pipeline_en_5.5.0_3.0_1727275102935.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_ner_pii_062024_pipeline_en_5.5.0_3.0_1727275102935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_ner_pii_062024_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_ner_pii_062024_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_ner_pii_062024_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/vuminhtue/Bert_large_NER_PII_062024 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline_en.md new file mode 100644 index 00000000000000..5b94900cb56414 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline pipeline BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline_en_5.5.0_3.0_1727288206598.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline_en_5.5.0_3.0_1727288206598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_deletion_multiclass_complete_final_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/research-dump/bert-large-uncased_deletion_multiclass_complete_final_v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_large_uncased_english_ner_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_large_uncased_english_ner_en.md new file mode 100644 index 00000000000000..c2e3fef4f27afb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_large_uncased_english_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_uncased_english_ner BertForTokenClassification from n6ai +author: John Snow Labs +name: bert_large_uncased_english_ner +date: 2024-09-25 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_english_ner` is a English model originally trained by n6ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_english_ner_en_5.5.0_3.0_1727281714961.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_english_ner_en_5.5.0_3.0_1727281714961.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_large_uncased_english_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_large_uncased_english_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_english_ner| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/n6ai/bert-large-uncased-en-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_mrpc_distilled_cka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_mrpc_distilled_cka_pipeline_en.md new file mode 100644 index 00000000000000..cff2007e659c24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_mrpc_distilled_cka_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mrpc_distilled_cka_pipeline pipeline BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: bert_mrpc_distilled_cka_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mrpc_distilled_cka_pipeline` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mrpc_distilled_cka_pipeline_en_5.5.0_3.0_1727268782656.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mrpc_distilled_cka_pipeline_en_5.5.0_3.0_1727268782656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mrpc_distilled_cka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mrpc_distilled_cka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mrpc_distilled_cka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|154.8 MB| + +## References + +https://huggingface.co/Sayan01/bert-mrpc-distilled-cka + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_mrpc_glue_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_mrpc_glue_pipeline_en.md new file mode 100644 index 00000000000000..eab245a5036350 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_mrpc_glue_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mrpc_glue_pipeline pipeline BertForSequenceClassification from itabrez +author: John Snow Labs +name: bert_mrpc_glue_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mrpc_glue_pipeline` is a English model originally trained by itabrez. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mrpc_glue_pipeline_en_5.5.0_3.0_1727307814045.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mrpc_glue_pipeline_en_5.5.0_3.0_1727307814045.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mrpc_glue_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mrpc_glue_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mrpc_glue_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/itabrez/bert-mrpc-glue + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_protein_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_protein_classifier_en.md new file mode 100644 index 00000000000000..6343e97cf793b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_protein_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_protein_classifier BertForSequenceClassification from oohtmeel +author: John Snow Labs +name: bert_protein_classifier +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_protein_classifier` is a English model originally trained by oohtmeel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_protein_classifier_en_5.5.0_3.0_1727266444155.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_protein_classifier_en_5.5.0_3.0_1727266444155.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_protein_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_protein_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_protein_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/oohtmeel/Bert_protein_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_sanskrit_saskta_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_sanskrit_saskta_test_pipeline_en.md new file mode 100644 index 00000000000000..6ae8d73bb13253 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_sanskrit_saskta_test_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sanskrit_saskta_test_pipeline pipeline BertForSequenceClassification from ilham14 +author: John Snow Labs +name: bert_sanskrit_saskta_test_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sanskrit_saskta_test_pipeline` is a English model originally trained by ilham14. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sanskrit_saskta_test_pipeline_en_5.5.0_3.0_1727273613568.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sanskrit_saskta_test_pipeline_en_5.5.0_3.0_1727273613568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sanskrit_saskta_test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sanskrit_saskta_test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sanskrit_saskta_test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|423.2 MB| + +## References + +https://huggingface.co/ilham14/BERT-SA-Test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_semaphore_prediction_w2_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_semaphore_prediction_w2_en.md new file mode 100644 index 00000000000000..5b25d60ec203dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_semaphore_prediction_w2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_semaphore_prediction_w2 BertForSequenceClassification from bondi +author: John Snow Labs +name: bert_semaphore_prediction_w2 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_semaphore_prediction_w2` is a English model originally trained by bondi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_semaphore_prediction_w2_en_5.5.0_3.0_1727284679659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_semaphore_prediction_w2_en_5.5.0_3.0_1727284679659.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_semaphore_prediction_w2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_semaphore_prediction_w2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_semaphore_prediction_w2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/bondi/bert-semaphore-prediction-w2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_twitter_english_lost_job_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_twitter_english_lost_job_en.md new file mode 100644 index 00000000000000..167de4fc25e39a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_twitter_english_lost_job_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English bert_twitter_english_lost_job BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_english_lost_job +date: 2024-09-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_english_lost_job_en_5.5.0_3.0_1727277508123.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_5.5.0_3.0_1727277508123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## 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 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.1 MB| + +## References + +References + +https://huggingface.co/manueltonneau/bert-twitter-en-lost-job \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-bert_twitterfin_padding0model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-bert_twitterfin_padding0model_pipeline_en.md new file mode 100644 index 00000000000000..2340d0e90e57da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-bert_twitterfin_padding0model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_twitterfin_padding0model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_twitterfin_padding0model_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitterfin_padding0model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding0model_pipeline_en_5.5.0_3.0_1727285764814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding0model_pipeline_en_5.5.0_3.0_1727285764814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_twitterfin_padding0model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_twitterfin_padding0model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitterfin_padding0model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_twitterfin_padding0model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-best_model_sst_2_16_21_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-best_model_sst_2_16_21_pipeline_en.md new file mode 100644 index 00000000000000..3db50ea44abe0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-best_model_sst_2_16_21_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English best_model_sst_2_16_21_pipeline pipeline BertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_sst_2_16_21_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_sst_2_16_21_pipeline` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_sst_2_16_21_pipeline_en_5.5.0_3.0_1727267017816.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_sst_2_16_21_pipeline_en_5.5.0_3.0_1727267017816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("best_model_sst_2_16_21_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("best_model_sst_2_16_21_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_sst_2_16_21_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/best_model-sst-2-16-21 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-biobert_huner_cell_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-biobert_huner_cell_v1_pipeline_en.md new file mode 100644 index 00000000000000..e2fa2f80f07bfa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-biobert_huner_cell_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English biobert_huner_cell_v1_pipeline pipeline BertForTokenClassification from aitslab +author: John Snow Labs +name: biobert_huner_cell_v1_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_huner_cell_v1_pipeline` is a English model originally trained by aitslab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_huner_cell_v1_pipeline_en_5.5.0_3.0_1727246243552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_huner_cell_v1_pipeline_en_5.5.0_3.0_1727246243552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("biobert_huner_cell_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("biobert_huner_cell_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobert_huner_cell_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/aitslab/biobert_huner_cell_v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-biobert_huner_disease_v1_en.md b/docs/_posts/ahmedlone127/2024-09-25-biobert_huner_disease_v1_en.md new file mode 100644 index 00000000000000..a203f6a2746293 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-biobert_huner_disease_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English biobert_huner_disease_v1 BertForTokenClassification from aitslab +author: John Snow Labs +name: biobert_huner_disease_v1 +date: 2024-09-25 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_huner_disease_v1` is a English model originally trained by aitslab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_huner_disease_v1_en_5.5.0_3.0_1727280419403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_huner_disease_v1_en_5.5.0_3.0_1727280419403.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') + +tokenClassifier = BertForTokenClassification.pretrained("biobert_huner_disease_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("biobert_huner_disease_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobert_huner_disease_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/aitslab/biobert_huner_disease_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-biobit_drugtemist_italian_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-biobit_drugtemist_italian_ner_pipeline_en.md new file mode 100644 index 00000000000000..146c2f310a8a93 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-biobit_drugtemist_italian_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English biobit_drugtemist_italian_ner_pipeline pipeline BertForTokenClassification from Rodrigo1771 +author: John Snow Labs +name: biobit_drugtemist_italian_ner_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobit_drugtemist_italian_ner_pipeline` is a English model originally trained by Rodrigo1771. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobit_drugtemist_italian_ner_pipeline_en_5.5.0_3.0_1727258976706.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobit_drugtemist_italian_ner_pipeline_en_5.5.0_3.0_1727258976706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("biobit_drugtemist_italian_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("biobit_drugtemist_italian_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobit_drugtemist_italian_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.2 MB| + +## References + +https://huggingface.co/Rodrigo1771/bioBIT-drugtemist-it-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en.md new file mode 100644 index 00000000000000..7390f0c944c36a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline pipeline BertForSequenceClassification from blizrys +author: John Snow Labs +name: biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline` is a English model originally trained by blizrys. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en_5.5.0_3.0_1727307250619.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en_5.5.0_3.0_1727307250619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.4 MB| + +## References + +https://huggingface.co/blizrys/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-boss_toxicity_24000_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-boss_toxicity_24000_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..e69bccc6cb3902 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-boss_toxicity_24000_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English boss_toxicity_24000_bert_base_uncased_pipeline pipeline BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: boss_toxicity_24000_bert_base_uncased_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`boss_toxicity_24000_bert_base_uncased_pipeline` is a English model originally trained by Kyle1668. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/boss_toxicity_24000_bert_base_uncased_pipeline_en_5.5.0_3.0_1727264097668.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boss_toxicity_24000_bert_base_uncased_pipeline_en_5.5.0_3.0_1727264097668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("boss_toxicity_24000_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("boss_toxicity_24000_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|boss_toxicity_24000_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/boss-toxicity-24000-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-camedbert_512_fl32_checkpoint_17386_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-25-camedbert_512_fl32_checkpoint_17386_pipeline_de.md new file mode 100644 index 00000000000000..e6cd4387f90d3d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-camedbert_512_fl32_checkpoint_17386_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German camedbert_512_fl32_checkpoint_17386_pipeline pipeline BertForTokenClassification from MSey +author: John Snow Labs +name: camedbert_512_fl32_checkpoint_17386_pipeline +date: 2024-09-25 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camedbert_512_fl32_checkpoint_17386_pipeline` is a German model originally trained by MSey. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camedbert_512_fl32_checkpoint_17386_pipeline_de_5.5.0_3.0_1727247145941.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camedbert_512_fl32_checkpoint_17386_pipeline_de_5.5.0_3.0_1727247145941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camedbert_512_fl32_checkpoint_17386_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camedbert_512_fl32_checkpoint_17386_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camedbert_512_fl32_checkpoint_17386_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|406.9 MB| + +## References + +https://huggingface.co/MSey/CaMedBERT-512_fl32_checkpoint-17386 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-cares_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-cares_bert_base_pipeline_en.md new file mode 100644 index 00000000000000..abd568b229ed38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-cares_bert_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cares_bert_base_pipeline pipeline BertForSequenceClassification from chizhikchi +author: John Snow Labs +name: cares_bert_base_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cares_bert_base_pipeline` is a English model originally trained by chizhikchi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cares_bert_base_pipeline_en_5.5.0_3.0_1727285284358.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cares_bert_base_pipeline_en_5.5.0_3.0_1727285284358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cares_bert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cares_bert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cares_bert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.8 MB| + +## References + +https://huggingface.co/chizhikchi/cares-bert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-case_analysis_inlegalbert_en.md b/docs/_posts/ahmedlone127/2024-09-25-case_analysis_inlegalbert_en.md new file mode 100644 index 00000000000000..90f8fa8d122f48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-case_analysis_inlegalbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English case_analysis_inlegalbert BertForSequenceClassification from cite-text-analysis +author: John Snow Labs +name: case_analysis_inlegalbert +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`case_analysis_inlegalbert` is a English model originally trained by cite-text-analysis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/case_analysis_inlegalbert_en_5.5.0_3.0_1727263733805.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/case_analysis_inlegalbert_en_5.5.0_3.0_1727263733805.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("case_analysis_inlegalbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("case_analysis_inlegalbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|case_analysis_inlegalbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cite-text-analysis/case-analysis-InLegalBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-chilean_spanish_hate_speech_es.md b/docs/_posts/ahmedlone127/2024-09-25-chilean_spanish_hate_speech_es.md new file mode 100644 index 00000000000000..98e16f24952227 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-chilean_spanish_hate_speech_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish chilean_spanish_hate_speech BertForSequenceClassification from jorgeortizfuentes +author: John Snow Labs +name: chilean_spanish_hate_speech +date: 2024-09-25 +tags: [es, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chilean_spanish_hate_speech` is a Castilian, Spanish model originally trained by jorgeortizfuentes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chilean_spanish_hate_speech_es_5.5.0_3.0_1727245858668.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chilean_spanish_hate_speech_es_5.5.0_3.0_1727245858668.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("chilean_spanish_hate_speech","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("chilean_spanish_hate_speech", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chilean_spanish_hate_speech| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.6 MB| + +## References + +https://huggingface.co/jorgeortizfuentes/chilean-spanish-hate-speech \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-chinese_roberta_climate_related_prediction_v1_en.md b/docs/_posts/ahmedlone127/2024-09-25-chinese_roberta_climate_related_prediction_v1_en.md new file mode 100644 index 00000000000000..07dbbb61bfb4e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-chinese_roberta_climate_related_prediction_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English chinese_roberta_climate_related_prediction_v1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: chinese_roberta_climate_related_prediction_v1 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_climate_related_prediction_v1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_related_prediction_v1_en_5.5.0_3.0_1727307359298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_related_prediction_v1_en_5.5.0_3.0_1727307359298.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("chinese_roberta_climate_related_prediction_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("chinese_roberta_climate_related_prediction_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_climate_related_prediction_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.2 MB| + +## References + +https://huggingface.co/hw2942/chinese-roberta-climate-related-prediction-V1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-clickbait_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-25-clickbait_spanish_es.md new file mode 100644 index 00000000000000..9b5032808019b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-clickbait_spanish_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish clickbait_spanish BertForSequenceClassification from taniwasl +author: John Snow Labs +name: clickbait_spanish +date: 2024-09-25 +tags: [es, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clickbait_spanish` is a Castilian, Spanish model originally trained by taniwasl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clickbait_spanish_es_5.5.0_3.0_1727293146997.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clickbait_spanish_es_5.5.0_3.0_1727293146997.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("clickbait_spanish","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("clickbait_spanish", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clickbait_spanish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/taniwasl/clickbait_es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-clinicalbert_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-clinicalbert_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..ce12998e96f817 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-clinicalbert_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English clinicalbert_finetuned_pipeline pipeline BertForSequenceClassification from SrinivasaPragada +author: John Snow Labs +name: clinicalbert_finetuned_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinicalbert_finetuned_pipeline` is a English model originally trained by SrinivasaPragada. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_pipeline_en_5.5.0_3.0_1727254510425.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinicalbert_finetuned_pipeline_en_5.5.0_3.0_1727254510425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clinicalbert_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clinicalbert_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinicalbert_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.6 MB| + +## References + +https://huggingface.co/SrinivasaPragada/clinicalbert-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-danish_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-danish_bert_pipeline_en.md new file mode 100644 index 00000000000000..72b3e6ab53a98b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-danish_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English danish_bert_pipeline pipeline BertEmbeddings from iolariu +author: John Snow Labs +name: danish_bert_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`danish_bert_pipeline` is a English model originally trained by iolariu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/danish_bert_pipeline_en_5.5.0_3.0_1727232607219.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/danish_bert_pipeline_en_5.5.0_3.0_1727232607219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("danish_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("danish_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|danish_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/iolariu/DA_BERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-detoxify_toxic_english_en.md b/docs/_posts/ahmedlone127/2024-09-25-detoxify_toxic_english_en.md new file mode 100644 index 00000000000000..ce8a0bae5cef02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-detoxify_toxic_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English detoxify_toxic_english BertForSequenceClassification from joshuahm +author: John Snow Labs +name: detoxify_toxic_english +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`detoxify_toxic_english` is a English model originally trained by joshuahm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/detoxify_toxic_english_en_5.5.0_3.0_1727290833002.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/detoxify_toxic_english_en_5.5.0_3.0_1727290833002.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("detoxify_toxic_english","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("detoxify_toxic_english", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|detoxify_toxic_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/joshuahm/detoxify_toxic_en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-dialogue2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-dialogue2_pipeline_en.md new file mode 100644 index 00000000000000..3b84a1782824ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-dialogue2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dialogue2_pipeline pipeline BertForSequenceClassification from SharonTudi +author: John Snow Labs +name: dialogue2_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dialogue2_pipeline` is a English model originally trained by SharonTudi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dialogue2_pipeline_en_5.5.0_3.0_1727289855298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dialogue2_pipeline_en_5.5.0_3.0_1727289855298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dialogue2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dialogue2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dialogue2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/SharonTudi/DIALOGUE2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-dummy_en.md b/docs/_posts/ahmedlone127/2024-09-25-dummy_en.md new file mode 100644 index 00000000000000..77951c4b2d80fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-dummy_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English dummy CamemBertForSequenceClassification from Longtong +author: John Snow Labs +name: dummy +date: 2024-09-25 +tags: [camembert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +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.`dummy` is a English model originally trained by Longtong. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_en_5.5.0_3.0_1727255259091.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_en_5.5.0_3.0_1727255259091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = CamemBertForSequenceClassification.pretrained("dummy","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.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("dummy","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|407.2 MB| + +## References + +References + +References + +https://huggingface.co/Longtong/dummy \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline_en.md new file mode 100644 index 00000000000000..2e1b1e24fed278 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline pipeline BertForSequenceClassification from harish +author: John Snow Labs +name: english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline` is a English model originally trained by harish. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline_en_5.5.0_3.0_1727277633054.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline_en_5.5.0_3.0_1727277633054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_astitchtask1a_bertbasecased_falsetrue_0_3_best_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/harish/EN-AStitchTask1A-BERTBaseCased-FalseTrue-0-3-BEST + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-english_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-english_base_pipeline_en.md new file mode 100644 index 00000000000000..701a02266db92f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-english_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English english_base_pipeline pipeline BertForTokenClassification from mudes +author: John Snow Labs +name: english_base_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_base_pipeline` is a English model originally trained by mudes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_base_pipeline_en_5.5.0_3.0_1727270424533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_base_pipeline_en_5.5.0_3.0_1727270424533.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("english_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("english_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/mudes/en-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline_en.md new file mode 100644 index 00000000000000..55919b66e7a759 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline pipeline BertForSequenceClassification from jacquesle +author: John Snow Labs +name: favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline` is a English model originally trained by jacquesle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline_en_5.5.0_3.0_1727276892851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline_en_5.5.0_3.0_1727276892851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|favs_filtersort_multilabel_classification_bert_base_cased_jacquesle_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jacquesle/favs-filtersort-multilabel-classification-bert-base-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-fine_tuned_bert_czech_wikann_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-fine_tuned_bert_czech_wikann_pipeline_en.md new file mode 100644 index 00000000000000..9a9bed9caf50d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-fine_tuned_bert_czech_wikann_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_bert_czech_wikann_pipeline pipeline BertForTokenClassification from stulcrad +author: John Snow Labs +name: fine_tuned_bert_czech_wikann_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_czech_wikann_pipeline` is a English model originally trained by stulcrad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_czech_wikann_pipeline_en_5.5.0_3.0_1727275520733.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_czech_wikann_pipeline_en_5.5.0_3.0_1727275520733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_bert_czech_wikann_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_bert_czech_wikann_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bert_czech_wikann_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/stulcrad/fine_tuned_BERT_cs_wikann + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-friends_emotions_detection_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-25-friends_emotions_detection_distilbert_en.md new file mode 100644 index 00000000000000..c50887ab323aec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-friends_emotions_detection_distilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English friends_emotions_detection_distilbert BertForSequenceClassification from dima806 +author: John Snow Labs +name: friends_emotions_detection_distilbert +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`friends_emotions_detection_distilbert` is a English model originally trained by dima806. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/friends_emotions_detection_distilbert_en_5.5.0_3.0_1727266378250.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/friends_emotions_detection_distilbert_en_5.5.0_3.0_1727266378250.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("friends_emotions_detection_distilbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("friends_emotions_detection_distilbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|friends_emotions_detection_distilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/dima806/friends-emotions-detection-distilbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-gpt2_20240904_005243_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-gpt2_20240904_005243_pipeline_en.md new file mode 100644 index 00000000000000..931f287bb68a25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-gpt2_20240904_005243_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gpt2_20240904_005243_pipeline pipeline BertForSequenceClassification from llavallava +author: John Snow Labs +name: gpt2_20240904_005243_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gpt2_20240904_005243_pipeline` is a English model originally trained by llavallava. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_20240904_005243_pipeline_en_5.5.0_3.0_1727276919000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_20240904_005243_pipeline_en_5.5.0_3.0_1727276919000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gpt2_20240904_005243_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gpt2_20240904_005243_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gpt2_20240904_005243_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/llavallava/gpt2-20240904_005243 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-hate_speech_slo_pipeline_sl.md b/docs/_posts/ahmedlone127/2024-09-25-hate_speech_slo_pipeline_sl.md new file mode 100644 index 00000000000000..9f62e0b73d5307 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-hate_speech_slo_pipeline_sl.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Slovenian hate_speech_slo_pipeline pipeline BertForSequenceClassification from IMSyPP +author: John Snow Labs +name: hate_speech_slo_pipeline +date: 2024-09-25 +tags: [sl, open_source, pipeline, onnx] +task: Text Classification +language: sl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_speech_slo_pipeline` is a Slovenian model originally trained by IMSyPP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hate_speech_slo_pipeline_sl_5.5.0_3.0_1727245744831.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_speech_slo_pipeline_sl_5.5.0_3.0_1727245744831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hate_speech_slo_pipeline", lang = "sl") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hate_speech_slo_pipeline", lang = "sl") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hate_speech_slo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|sl| +|Size:|465.7 MB| + +## References + +https://huggingface.co/IMSyPP/hate_speech_slo + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-human_needs_albert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-human_needs_albert_pipeline_en.md new file mode 100644 index 00000000000000..e0de3586100079 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-human_needs_albert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English human_needs_albert_pipeline pipeline BertForSequenceClassification from zzhifz +author: John Snow Labs +name: human_needs_albert_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`human_needs_albert_pipeline` is a English model originally trained by zzhifz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/human_needs_albert_pipeline_en_5.5.0_3.0_1727253778655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/human_needs_albert_pipeline_en_5.5.0_3.0_1727253778655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("human_needs_albert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("human_needs_albert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|human_needs_albert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/zzhifz/human-needs-albert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-hyp_only_gpt_4_filtered_final_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-hyp_only_gpt_4_filtered_final_pipeline_en.md new file mode 100644 index 00000000000000..12055cfa2170e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-hyp_only_gpt_4_filtered_final_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hyp_only_gpt_4_filtered_final_pipeline pipeline BertForSequenceClassification from grace-pro +author: John Snow Labs +name: hyp_only_gpt_4_filtered_final_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hyp_only_gpt_4_filtered_final_pipeline` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hyp_only_gpt_4_filtered_final_pipeline_en_5.5.0_3.0_1727304603177.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hyp_only_gpt_4_filtered_final_pipeline_en_5.5.0_3.0_1727304603177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hyp_only_gpt_4_filtered_final_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hyp_only_gpt_4_filtered_final_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hyp_only_gpt_4_filtered_final_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/hyp_only_gpt_4_filtered_final + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline_en.md new file mode 100644 index 00000000000000..437750fcf7fdc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline pipeline BertForSequenceClassification from edmejiat +author: John Snow Labs +name: imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline` is a English model originally trained by edmejiat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline_en_5.5.0_3.0_1727297984746.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline_en_5.5.0_3.0_1727297984746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imdbreviews_classification_distilbert_v02_clf_finetuning_edmejiat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|626.9 MB| + +## References + +https://huggingface.co/edmejiat/imdbreviews_classification_distilbert_v02_clf_finetuning + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-kemenkeu_sentiment_classifier_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-25-kemenkeu_sentiment_classifier_pipeline_id.md new file mode 100644 index 00000000000000..775c8c55239167 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-kemenkeu_sentiment_classifier_pipeline_id.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Indonesian kemenkeu_sentiment_classifier_pipeline pipeline BertForSequenceClassification from hanifnoerr +author: John Snow Labs +name: kemenkeu_sentiment_classifier_pipeline +date: 2024-09-25 +tags: [id, open_source, pipeline, onnx] +task: Text Classification +language: id +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kemenkeu_sentiment_classifier_pipeline` is a Indonesian model originally trained by hanifnoerr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kemenkeu_sentiment_classifier_pipeline_id_5.5.0_3.0_1727305152615.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kemenkeu_sentiment_classifier_pipeline_id_5.5.0_3.0_1727305152615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("kemenkeu_sentiment_classifier_pipeline", lang = "id") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("kemenkeu_sentiment_classifier_pipeline", lang = "id") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kemenkeu_sentiment_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|id| +|Size:|466.4 MB| + +## References + +https://huggingface.co/hanifnoerr/Kemenkeu-Sentiment-Classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-l_12_h_512_a_8_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-l_12_h_512_a_8_sst2_pipeline_en.md new file mode 100644 index 00000000000000..c8e2c608a6d317 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-l_12_h_512_a_8_sst2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English l_12_h_512_a_8_sst2_pipeline pipeline BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: l_12_h_512_a_8_sst2_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`l_12_h_512_a_8_sst2_pipeline` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/l_12_h_512_a_8_sst2_pipeline_en_5.5.0_3.0_1727267405872.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/l_12_h_512_a_8_sst2_pipeline_en_5.5.0_3.0_1727267405872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("l_12_h_512_a_8_sst2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("l_12_h_512_a_8_sst2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|l_12_h_512_a_8_sst2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|202.5 MB| + +## References + +https://huggingface.co/Sayan01/L-12_H-512_A-8_sst2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-learn2therm_en.md b/docs/_posts/ahmedlone127/2024-09-25-learn2therm_en.md new file mode 100644 index 00000000000000..a3cdbee3116aeb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-learn2therm_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English learn2therm BertForSequenceClassification from evankomp +author: John Snow Labs +name: learn2therm +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`learn2therm` is a English model originally trained by evankomp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/learn2therm_en_5.5.0_3.0_1727304788735.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/learn2therm_en_5.5.0_3.0_1727304788735.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("learn2therm","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("learn2therm", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|learn2therm| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/evankomp/learn2therm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-legal_ner_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-legal_ner_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..46179fff7b7654 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-legal_ner_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English legal_ner_finetuned_pipeline pipeline BertForTokenClassification from AjayMukundS +author: John Snow Labs +name: legal_ner_finetuned_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_ner_finetuned_pipeline` is a English model originally trained by AjayMukundS. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_ner_finetuned_pipeline_en_5.5.0_3.0_1727271246417.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_ner_finetuned_pipeline_en_5.5.0_3.0_1727271246417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legal_ner_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legal_ner_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_ner_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/AjayMukundS/Legal-NER-Finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-legalis_bert_de.md b/docs/_posts/ahmedlone127/2024-09-25-legalis_bert_de.md new file mode 100644 index 00000000000000..a6466d7062422e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-legalis_bert_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German legalis_bert BertForSequenceClassification from LennardZuendorf +author: John Snow Labs +name: legalis_bert +date: 2024-09-25 +tags: [de, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legalis_bert` is a German model originally trained by LennardZuendorf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legalis_bert_de_5.5.0_3.0_1727279255098.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legalis_bert_de_5.5.0_3.0_1727279255098.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("legalis_bert","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("legalis_bert", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legalis_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|412.0 MB| + +## References + +https://huggingface.co/LennardZuendorf/legalis-BERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-lngdistilledmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-lngdistilledmodel_pipeline_en.md new file mode 100644 index 00000000000000..dd131eeaa80b6b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-lngdistilledmodel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lngdistilledmodel_pipeline pipeline BertForSequenceClassification from privacy-tech-lab +author: John Snow Labs +name: lngdistilledmodel_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lngdistilledmodel_pipeline` is a English model originally trained by privacy-tech-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lngdistilledmodel_pipeline_en_5.5.0_3.0_1727272895317.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lngdistilledmodel_pipeline_en_5.5.0_3.0_1727272895317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lngdistilledmodel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lngdistilledmodel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lngdistilledmodel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/privacy-tech-lab/LngDistilledModel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-mitre_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2024-09-25-mitre_bert_base_cased_en.md new file mode 100644 index 00000000000000..c59cf08014e45a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-mitre_bert_base_cased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mitre_bert_base_cased BertForSequenceClassification from bencyc1129 +author: John Snow Labs +name: mitre_bert_base_cased +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mitre_bert_base_cased` is a English model originally trained by bencyc1129. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mitre_bert_base_cased_en_5.5.0_3.0_1727266928655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mitre_bert_base_cased_en_5.5.0_3.0_1727266928655.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("mitre_bert_base_cased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mitre_bert_base_cased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mitre_bert_base_cased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/bencyc1129/mitre-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-modlee_transformer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-modlee_transformer_pipeline_en.md new file mode 100644 index 00000000000000..8f22b0edc694ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-modlee_transformer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English modlee_transformer_pipeline pipeline BertForSequenceClassification from harshitakukreja +author: John Snow Labs +name: modlee_transformer_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`modlee_transformer_pipeline` is a English model originally trained by harshitakukreja. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/modlee_transformer_pipeline_en_5.5.0_3.0_1727273293593.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/modlee_transformer_pipeline_en_5.5.0_3.0_1727273293593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("modlee_transformer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("modlee_transformer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|modlee_transformer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/harshitakukreja/modlee_transformer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-movie_genre_classifier_davooddkareshki_en.md b/docs/_posts/ahmedlone127/2024-09-25-movie_genre_classifier_davooddkareshki_en.md new file mode 100644 index 00000000000000..20951cb62ba0b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-movie_genre_classifier_davooddkareshki_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English movie_genre_classifier_davooddkareshki BertForSequenceClassification from davooddkareshki +author: John Snow Labs +name: movie_genre_classifier_davooddkareshki +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_genre_classifier_davooddkareshki` is a English model originally trained by davooddkareshki. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_genre_classifier_davooddkareshki_en_5.5.0_3.0_1727277453434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_genre_classifier_davooddkareshki_en_5.5.0_3.0_1727277453434.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("movie_genre_classifier_davooddkareshki","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("movie_genre_classifier_davooddkareshki", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|movie_genre_classifier_davooddkareshki| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/davooddkareshki/Movie_Genre_Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-n_bert_imdb_padding20model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-n_bert_imdb_padding20model_pipeline_en.md new file mode 100644 index 00000000000000..80d2c634aec309 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-n_bert_imdb_padding20model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_bert_imdb_padding20model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_imdb_padding20model_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_imdb_padding20model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding20model_pipeline_en_5.5.0_3.0_1727267454468.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding20model_pipeline_en_5.5.0_3.0_1727267454468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_bert_imdb_padding20model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_bert_imdb_padding20model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_imdb_padding20model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Realgon/N_bert_imdb_padding20model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-n_bert_sst5_padding10model_en.md b/docs/_posts/ahmedlone127/2024-09-25-n_bert_sst5_padding10model_en.md new file mode 100644 index 00000000000000..920ebddb1312f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-n_bert_sst5_padding10model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_sst5_padding10model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_sst5_padding10model +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_sst5_padding10model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding10model_en_5.5.0_3.0_1727279747352.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding10model_en_5.5.0_3.0_1727279747352.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("n_bert_sst5_padding10model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_sst5_padding10model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_sst5_padding10model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/N_bert_sst5_padding10model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-n_bert_twitterfin_padding60model_en.md b/docs/_posts/ahmedlone127/2024-09-25-n_bert_twitterfin_padding60model_en.md new file mode 100644 index 00000000000000..122ebbb397f180 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-n_bert_twitterfin_padding60model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_twitterfin_padding60model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_twitterfin_padding60model +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_twitterfin_padding60model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_twitterfin_padding60model_en_5.5.0_3.0_1727286166126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_twitterfin_padding60model_en_5.5.0_3.0_1727286166126.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("n_bert_twitterfin_padding60model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_twitterfin_padding60model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_twitterfin_padding60model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Realgon/N_bert_twitterfin_padding60model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-n_bert_twitterfin_padding90model_en.md b/docs/_posts/ahmedlone127/2024-09-25-n_bert_twitterfin_padding90model_en.md new file mode 100644 index 00000000000000..14992e62adbfc8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-n_bert_twitterfin_padding90model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_twitterfin_padding90model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_twitterfin_padding90model +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_twitterfin_padding90model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_twitterfin_padding90model_en_5.5.0_3.0_1727279566226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_twitterfin_padding90model_en_5.5.0_3.0_1727279566226.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("n_bert_twitterfin_padding90model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_twitterfin_padding90model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_twitterfin_padding90model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/Realgon/N_bert_twitterfin_padding90model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-nameattrsbertfinal_en.md b/docs/_posts/ahmedlone127/2024-09-25-nameattrsbertfinal_en.md new file mode 100644 index 00000000000000..0e797171af1e16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-nameattrsbertfinal_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nameattrsbertfinal BertForSequenceClassification from madgnome +author: John Snow Labs +name: nameattrsbertfinal +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nameattrsbertfinal` is a English model originally trained by madgnome. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nameattrsbertfinal_en_5.5.0_3.0_1727293797937.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nameattrsbertfinal_en_5.5.0_3.0_1727293797937.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("nameattrsbertfinal","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("nameattrsbertfinal", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nameattrsbertfinal| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|668.9 MB| + +## References + +https://huggingface.co/madgnome/nameattrsbertfinal \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-newsbert_en.md b/docs/_posts/ahmedlone127/2024-09-25-newsbert_en.md new file mode 100644 index 00000000000000..6515ca2782e0aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-newsbert_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English newsbert BertEmbeddings from uclanlp +author: John Snow Labs +name: newsbert +date: 2024-09-25 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newsbert` is a English model originally trained by uclanlp. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newsbert_en_5.5.0_3.0_1727231936907.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newsbert_en_5.5.0_3.0_1727231936907.zip){:.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 =BertEmbeddings.pretrained("newsbert","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 = BertEmbeddings + .pretrained("newsbert", "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:|newsbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[bert]| +|Language:|en| +|Size:|407.1 MB| + +## References + +References + +https://huggingface.co/uclanlp/newsbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-newsbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-newsbert_pipeline_en.md new file mode 100644 index 00000000000000..9522aeb843f666 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-newsbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English newsbert_pipeline pipeline BertEmbeddings from psmeros +author: John Snow Labs +name: newsbert_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newsbert_pipeline` is a English model originally trained by psmeros. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newsbert_pipeline_en_5.5.0_3.0_1727231957617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newsbert_pipeline_en_5.5.0_3.0_1727231957617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("newsbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("newsbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|newsbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/psmeros/NewsBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-nusabert_base_indonesian_plutchik_emotion_analysis_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-25-nusabert_base_indonesian_plutchik_emotion_analysis_pipeline_id.md new file mode 100644 index 00000000000000..78f44c7b355915 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-nusabert_base_indonesian_plutchik_emotion_analysis_pipeline_id.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Indonesian nusabert_base_indonesian_plutchik_emotion_analysis_pipeline pipeline BertForSequenceClassification from Aardiiiiy +author: John Snow Labs +name: nusabert_base_indonesian_plutchik_emotion_analysis_pipeline +date: 2024-09-25 +tags: [id, open_source, pipeline, onnx] +task: Text Classification +language: id +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nusabert_base_indonesian_plutchik_emotion_analysis_pipeline` is a Indonesian model originally trained by Aardiiiiy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nusabert_base_indonesian_plutchik_emotion_analysis_pipeline_id_5.5.0_3.0_1727238076463.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nusabert_base_indonesian_plutchik_emotion_analysis_pipeline_id_5.5.0_3.0_1727238076463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nusabert_base_indonesian_plutchik_emotion_analysis_pipeline", lang = "id") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nusabert_base_indonesian_plutchik_emotion_analysis_pipeline", lang = "id") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nusabert_base_indonesian_plutchik_emotion_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|id| +|Size:|414.6 MB| + +## References + +https://huggingface.co/Aardiiiiy/NusaBERT-base-Indonesian-Plutchik-emotion-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-phishing_email_detection1_en.md b/docs/_posts/ahmedlone127/2024-09-25-phishing_email_detection1_en.md new file mode 100644 index 00000000000000..3f4ce087cd5e28 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-phishing_email_detection1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English phishing_email_detection1 BertForSequenceClassification from kithangw +author: John Snow Labs +name: phishing_email_detection1 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phishing_email_detection1` is a English model originally trained by kithangw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phishing_email_detection1_en_5.5.0_3.0_1727269658773.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phishing_email_detection1_en_5.5.0_3.0_1727269658773.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("phishing_email_detection1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("phishing_email_detection1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phishing_email_detection1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/kithangw/phishing_email_detection1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-phrasebank_sentiment_analysis_snrism_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-phrasebank_sentiment_analysis_snrism_pipeline_en.md new file mode 100644 index 00000000000000..0f4a57e400e0c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-phrasebank_sentiment_analysis_snrism_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_snrism_pipeline pipeline BertForSequenceClassification from snrism +author: John Snow Labs +name: phrasebank_sentiment_analysis_snrism_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_snrism_pipeline` is a English model originally trained by snrism. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_snrism_pipeline_en_5.5.0_3.0_1727301070425.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_snrism_pipeline_en_5.5.0_3.0_1727301070425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_snrism_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_snrism_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_snrism_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/snrism/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-quantum_neuraladaptivelearningsystem_en.md b/docs/_posts/ahmedlone127/2024-09-25-quantum_neuraladaptivelearningsystem_en.md new file mode 100644 index 00000000000000..03f95aa2224242 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-quantum_neuraladaptivelearningsystem_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English quantum_neuraladaptivelearningsystem BertForSequenceClassification from ayjays132 +author: John Snow Labs +name: quantum_neuraladaptivelearningsystem +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`quantum_neuraladaptivelearningsystem` is a English model originally trained by ayjays132. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/quantum_neuraladaptivelearningsystem_en_5.5.0_3.0_1727294020278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/quantum_neuraladaptivelearningsystem_en_5.5.0_3.0_1727294020278.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("quantum_neuraladaptivelearningsystem","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("quantum_neuraladaptivelearningsystem", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|quantum_neuraladaptivelearningsystem| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.1 MB| + +## References + +https://huggingface.co/ayjays132/Quantum-NeuralAdaptiveLearningSystem \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-re2g_reranker_fever_en.md b/docs/_posts/ahmedlone127/2024-09-25-re2g_reranker_fever_en.md new file mode 100644 index 00000000000000..2a4f7e39604da9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-re2g_reranker_fever_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English re2g_reranker_fever BertForSequenceClassification from ibm +author: John Snow Labs +name: re2g_reranker_fever +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`re2g_reranker_fever` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/re2g_reranker_fever_en_5.5.0_3.0_1727287223273.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/re2g_reranker_fever_en_5.5.0_3.0_1727287223273.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("re2g_reranker_fever","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("re2g_reranker_fever", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|re2g_reranker_fever| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ibm/re2g-reranker-fever \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-regbert_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-regbert_2_pipeline_en.md new file mode 100644 index 00000000000000..0c593bca0997de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-regbert_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English regbert_2_pipeline pipeline BertForSequenceClassification from Econlinguistics +author: John Snow Labs +name: regbert_2_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`regbert_2_pipeline` is a English model originally trained by Econlinguistics. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/regbert_2_pipeline_en_5.5.0_3.0_1727306366791.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/regbert_2_pipeline_en_5.5.0_3.0_1727306366791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("regbert_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("regbert_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|regbert_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Econlinguistics/regbert_2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-reranker_ent_synonyms_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-reranker_ent_synonyms_pipeline_en.md new file mode 100644 index 00000000000000..5514744dbcfea9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-reranker_ent_synonyms_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English reranker_ent_synonyms_pipeline pipeline BertForSequenceClassification from PitKoro +author: John Snow Labs +name: reranker_ent_synonyms_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reranker_ent_synonyms_pipeline` is a English model originally trained by PitKoro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reranker_ent_synonyms_pipeline_en_5.5.0_3.0_1727276823612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reranker_ent_synonyms_pipeline_en_5.5.0_3.0_1727276823612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("reranker_ent_synonyms_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("reranker_ent_synonyms_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reranker_ent_synonyms_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|627.8 MB| + +## References + +https://huggingface.co/PitKoro/reranker_ent_synonyms + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-response_score_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-response_score_pipeline_en.md new file mode 100644 index 00000000000000..c51412fa74195b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-response_score_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English response_score_pipeline pipeline BertForSequenceClassification from conversify +author: John Snow Labs +name: response_score_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`response_score_pipeline` is a English model originally trained by conversify. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/response_score_pipeline_en_5.5.0_3.0_1727279132795.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/response_score_pipeline_en_5.5.0_3.0_1727279132795.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("response_score_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("response_score_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|response_score_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/conversify/response-score + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-roberta_finetuned_domains_en.md b/docs/_posts/ahmedlone127/2024-09-25-roberta_finetuned_domains_en.md new file mode 100644 index 00000000000000..bdcab050f53368 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-roberta_finetuned_domains_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_finetuned_domains BertForSequenceClassification from redscroll +author: John Snow Labs +name: roberta_finetuned_domains +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_finetuned_domains` is a English model originally trained by redscroll. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_domains_en_5.5.0_3.0_1727294359470.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_domains_en_5.5.0_3.0_1727294359470.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("roberta_finetuned_domains","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("roberta_finetuned_domains", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_domains| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/redscroll/roberta-finetuned-domains \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-rubert_tiny2_russe_toxicity_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-rubert_tiny2_russe_toxicity_pipeline_en.md new file mode 100644 index 00000000000000..1c645f56b655b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-rubert_tiny2_russe_toxicity_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English rubert_tiny2_russe_toxicity_pipeline pipeline BertForSequenceClassification from BunnyNoBugs +author: John Snow Labs +name: rubert_tiny2_russe_toxicity_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny2_russe_toxicity_pipeline` is a English model originally trained by BunnyNoBugs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_russe_toxicity_pipeline_en_5.5.0_3.0_1727278798442.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_russe_toxicity_pipeline_en_5.5.0_3.0_1727278798442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rubert_tiny2_russe_toxicity_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rubert_tiny2_russe_toxicity_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_tiny2_russe_toxicity_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|109.5 MB| + +## References + +https://huggingface.co/BunnyNoBugs/rubert-tiny2-russe-toxicity + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sarcasm_detection_bert_base_uncased_cree_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-sarcasm_detection_bert_base_uncased_cree_pipeline_en.md new file mode 100644 index 00000000000000..e8cd59a4fece79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sarcasm_detection_bert_base_uncased_cree_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sarcasm_detection_bert_base_uncased_cree_pipeline pipeline BertForSequenceClassification from jkhan447 +author: John Snow Labs +name: sarcasm_detection_bert_base_uncased_cree_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sarcasm_detection_bert_base_uncased_cree_pipeline` is a English model originally trained by jkhan447. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sarcasm_detection_bert_base_uncased_cree_pipeline_en_5.5.0_3.0_1727263833210.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sarcasm_detection_bert_base_uncased_cree_pipeline_en_5.5.0_3.0_1727263833210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sarcasm_detection_bert_base_uncased_cree_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sarcasm_detection_bert_base_uncased_cree_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sarcasm_detection_bert_base_uncased_cree_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jkhan447/sarcasm-detection-Bert-base-uncased-CR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-savedaftertrainingtest39_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-savedaftertrainingtest39_pipeline_en.md new file mode 100644 index 00000000000000..0dc7a2caa24663 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-savedaftertrainingtest39_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English savedaftertrainingtest39_pipeline pipeline BertForSequenceClassification from NTCAL +author: John Snow Labs +name: savedaftertrainingtest39_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`savedaftertrainingtest39_pipeline` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/savedaftertrainingtest39_pipeline_en_5.5.0_3.0_1727284713270.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/savedaftertrainingtest39_pipeline_en_5.5.0_3.0_1727284713270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("savedaftertrainingtest39_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("savedaftertrainingtest39_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|savedaftertrainingtest39_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|467.4 MB| + +## References + +https://huggingface.co/NTCAL/SavedAfterTrainingTest39 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-scenario_tcr_data_glue_sst2_model_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-25-scenario_tcr_data_glue_sst2_model_bert_base_uncased_en.md new file mode 100644 index 00000000000000..71cdff13c4bd34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-scenario_tcr_data_glue_sst2_model_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English scenario_tcr_data_glue_sst2_model_bert_base_uncased BertForSequenceClassification from haryoaw +author: John Snow Labs +name: scenario_tcr_data_glue_sst2_model_bert_base_uncased +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_glue_sst2_model_bert_base_uncased` is a English model originally trained by haryoaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_sst2_model_bert_base_uncased_en_5.5.0_3.0_1727308677699.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_sst2_model_bert_base_uncased_en_5.5.0_3.0_1727308677699.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("scenario_tcr_data_glue_sst2_model_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scenario_tcr_data_glue_sst2_model_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_tcr_data_glue_sst2_model_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/haryoaw/scenario-TCR-data-glue-sst2-model-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..bec86695816193 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline pipeline BertForSequenceClassification from haryoaw +author: John Snow Labs +name: scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline` is a English model originally trained by haryoaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727308699593.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727308699593.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_tcr_data_glue_sst2_model_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/haryoaw/scenario-TCR-data-glue-sst2-model-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sead_l_6_h_256_a_8_mrpc_en.md b/docs/_posts/ahmedlone127/2024-09-25-sead_l_6_h_256_a_8_mrpc_en.md new file mode 100644 index 00000000000000..5b765db117dda7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sead_l_6_h_256_a_8_mrpc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sead_l_6_h_256_a_8_mrpc BertForSequenceClassification from C5i +author: John Snow Labs +name: sead_l_6_h_256_a_8_mrpc +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sead_l_6_h_256_a_8_mrpc` is a English model originally trained by C5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sead_l_6_h_256_a_8_mrpc_en_5.5.0_3.0_1727256755674.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sead_l_6_h_256_a_8_mrpc_en_5.5.0_3.0_1727256755674.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("sead_l_6_h_256_a_8_mrpc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sead_l_6_h_256_a_8_mrpc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sead_l_6_h_256_a_8_mrpc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|47.3 MB| + +## References + +https://huggingface.co/C5i/SEAD-L-6_H-256_A-8-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sead_l_6_h_384_a_12_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-sead_l_6_h_384_a_12_rte_pipeline_en.md new file mode 100644 index 00000000000000..5e65d716c8d64c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sead_l_6_h_384_a_12_rte_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sead_l_6_h_384_a_12_rte_pipeline pipeline BertForSequenceClassification from C5i +author: John Snow Labs +name: sead_l_6_h_384_a_12_rte_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sead_l_6_h_384_a_12_rte_pipeline` is a English model originally trained by C5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sead_l_6_h_384_a_12_rte_pipeline_en_5.5.0_3.0_1727304375120.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sead_l_6_h_384_a_12_rte_pipeline_en_5.5.0_3.0_1727304375120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sead_l_6_h_384_a_12_rte_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sead_l_6_h_384_a_12_rte_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sead_l_6_h_384_a_12_rte_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|84.2 MB| + +## References + +https://huggingface.co/C5i/SEAD-L-6_H-384_A-12-rte + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_english_french_italian_cased_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_english_french_italian_cased_en.md new file mode 100644 index 00000000000000..5e58cb5463b99b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_english_french_italian_cased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_base_english_french_italian_cased BertSentenceEmbeddings from Geotrend +author: John Snow Labs +name: sent_bert_base_english_french_italian_cased +date: 2024-09-25 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_english_french_italian_cased` is a English model originally trained by Geotrend. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_italian_cased_en_5.5.0_3.0_1727248897006.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_italian_cased_en_5.5.0_3.0_1727248897006.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_english_french_italian_cased","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_english_french_italian_cased","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_english_french_italian_cased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|428.1 MB| + +## References + +https://huggingface.co/Geotrend/bert-base-en-fr-it-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline_en.md new file mode 100644 index 00000000000000..1cf8b62edb7488 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline pipeline BertSentenceEmbeddings from rman-rahimi-29 +author: John Snow Labs +name: sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline` is a English model originally trained by rman-rahimi-29. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline_en_5.5.0_3.0_1727231023675.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline_en_5.5.0_3.0_1727231023675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_uncased_finetuned_imdb_rman_rahimi_29_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.7 MB| + +## References + +https://huggingface.co/rman-rahimi-29/bert-base-uncased-finetuned-imdb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_issues_128_mabrouk_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_issues_128_mabrouk_en.md new file mode 100644 index 00000000000000..2ac517fb6420ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_issues_128_mabrouk_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_base_uncased_issues_128_mabrouk BertSentenceEmbeddings from mabrouk +author: John Snow Labs +name: sent_bert_base_uncased_issues_128_mabrouk +date: 2024-09-25 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_issues_128_mabrouk` is a English model originally trained by mabrouk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_mabrouk_en_5.5.0_3.0_1727251436102.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_issues_128_mabrouk_en_5.5.0_3.0_1727251436102.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_issues_128_mabrouk","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_issues_128_mabrouk","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_uncased_issues_128_mabrouk| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/mabrouk/bert-base-uncased-issues-128 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_model_attribution_challenge_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_model_attribution_challenge_pipeline_en.md new file mode 100644 index 00000000000000..6fbe22a5a8e02e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_model_attribution_challenge_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bert_base_uncased_model_attribution_challenge_pipeline pipeline BertSentenceEmbeddings from model-attribution-challenge +author: John Snow Labs +name: sent_bert_base_uncased_model_attribution_challenge_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_model_attribution_challenge_pipeline` is a English model originally trained by model-attribution-challenge. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_model_attribution_challenge_pipeline_en_5.5.0_3.0_1727252057375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_model_attribution_challenge_pipeline_en_5.5.0_3.0_1727252057375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_base_uncased_model_attribution_challenge_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_base_uncased_model_attribution_challenge_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_uncased_model_attribution_challenge_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.7 MB| + +## References + +https://huggingface.co/model-attribution-challenge/bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_sclarge_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_sclarge_en.md new file mode 100644 index 00000000000000..dfd50e3a7aa5bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_base_uncased_sclarge_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_base_uncased_sclarge BertSentenceEmbeddings from CambridgeMolecularEngineering +author: John Snow Labs +name: sent_bert_base_uncased_sclarge +date: 2024-09-25 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_uncased_sclarge` is a English model originally trained by CambridgeMolecularEngineering. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_sclarge_en_5.5.0_3.0_1727230859963.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_uncased_sclarge_en_5.5.0_3.0_1727230859963.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_sclarge","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_uncased_sclarge","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_uncased_sclarge| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/CambridgeMolecularEngineering/bert-base-uncased-sclarge \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_bert_large_portuguese_cased_legal_tsdae_pt.md b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_large_portuguese_cased_legal_tsdae_pt.md new file mode 100644 index 00000000000000..a260be9216742b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_bert_large_portuguese_cased_legal_tsdae_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese sent_bert_large_portuguese_cased_legal_tsdae BertSentenceEmbeddings from stjiris +author: John Snow Labs +name: sent_bert_large_portuguese_cased_legal_tsdae +date: 2024-09-25 +tags: [pt, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_portuguese_cased_legal_tsdae` is a Portuguese model originally trained by stjiris. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_portuguese_cased_legal_tsdae_pt_5.5.0_3.0_1727253308090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_portuguese_cased_legal_tsdae_pt_5.5.0_3.0_1727253308090.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_portuguese_cased_legal_tsdae","pt") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_portuguese_cased_legal_tsdae","pt") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_large_portuguese_cased_legal_tsdae| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|pt| +|Size:|1.2 GB| + +## References + +https://huggingface.co/stjiris/bert-large-portuguese-cased-legal-tsdae \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_bio_bert_base_spanish_wwm_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_bio_bert_base_spanish_wwm_cased_pipeline_en.md new file mode 100644 index 00000000000000..a9356be37feaa4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_bio_bert_base_spanish_wwm_cased_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bio_bert_base_spanish_wwm_cased_pipeline pipeline BertSentenceEmbeddings from mrojas +author: John Snow Labs +name: sent_bio_bert_base_spanish_wwm_cased_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bio_bert_base_spanish_wwm_cased_pipeline` is a English model originally trained by mrojas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bio_bert_base_spanish_wwm_cased_pipeline_en_5.5.0_3.0_1727252478396.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bio_bert_base_spanish_wwm_cased_pipeline_en_5.5.0_3.0_1727252478396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bio_bert_base_spanish_wwm_cased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bio_bert_base_spanish_wwm_cased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bio_bert_base_spanish_wwm_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/mrojas/bio-bert-base-spanish-wwm-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_cl_arabertv0_1_base_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_cl_arabertv0_1_base_en.md new file mode 100644 index 00000000000000..fdb2b814c74ca2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_cl_arabertv0_1_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_cl_arabertv0_1_base BertSentenceEmbeddings from qahq +author: John Snow Labs +name: sent_cl_arabertv0_1_base +date: 2024-09-25 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cl_arabertv0_1_base` is a English model originally trained by qahq. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_cl_arabertv0_1_base_en_5.5.0_3.0_1727251572826.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cl_arabertv0_1_base_en_5.5.0_3.0_1727251572826.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_cl_arabertv0_1_base","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_cl_arabertv0_1_base","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_cl_arabertv0_1_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|505.0 MB| + +## References + +https://huggingface.co/qahq/CL-AraBERTv0.1-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_melayubert_ms.md b/docs/_posts/ahmedlone127/2024-09-25-sent_melayubert_ms.md new file mode 100644 index 00000000000000..317f7b9246b25d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_melayubert_ms.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Malay (macrolanguage) sent_melayubert BertSentenceEmbeddings from StevenLimcorn +author: John Snow Labs +name: sent_melayubert +date: 2024-09-25 +tags: [ms, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: ms +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_melayubert` is a Malay (macrolanguage) model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_melayubert_ms_5.5.0_3.0_1727252940005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_melayubert_ms_5.5.0_3.0_1727252940005.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_melayubert","ms") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_melayubert","ms") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_melayubert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|ms| +|Size:|408.1 MB| + +## References + +https://huggingface.co/StevenLimcorn/MelayuBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_melayubert_pipeline_ms.md b/docs/_posts/ahmedlone127/2024-09-25-sent_melayubert_pipeline_ms.md new file mode 100644 index 00000000000000..dffab4147724b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_melayubert_pipeline_ms.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Malay (macrolanguage) sent_melayubert_pipeline pipeline BertSentenceEmbeddings from StevenLimcorn +author: John Snow Labs +name: sent_melayubert_pipeline +date: 2024-09-25 +tags: [ms, open_source, pipeline, onnx] +task: Embeddings +language: ms +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_melayubert_pipeline` is a Malay (macrolanguage) model originally trained by StevenLimcorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_melayubert_pipeline_ms_5.5.0_3.0_1727252961221.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_melayubert_pipeline_ms_5.5.0_3.0_1727252961221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_melayubert_pipeline", lang = "ms") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_melayubert_pipeline", lang = "ms") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_melayubert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ms| +|Size:|408.7 MB| + +## References + +https://huggingface.co/StevenLimcorn/MelayuBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_newsbert_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_newsbert_en.md new file mode 100644 index 00000000000000..cb42b59858856f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_newsbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_newsbert BertSentenceEmbeddings from psmeros +author: John Snow Labs +name: sent_newsbert +date: 2024-09-25 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_newsbert` is a English model originally trained by psmeros. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_newsbert_en_5.5.0_3.0_1727251613432.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_newsbert_en_5.5.0_3.0_1727251613432.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_newsbert","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_newsbert","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_newsbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/psmeros/NewsBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-sent_scholarbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-sent_scholarbert_pipeline_en.md new file mode 100644 index 00000000000000..61d31e8fee2a9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-sent_scholarbert_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_scholarbert_pipeline pipeline BertSentenceEmbeddings from globuslabs +author: John Snow Labs +name: sent_scholarbert_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_scholarbert_pipeline` is a English model originally trained by globuslabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_scholarbert_pipeline_en_5.5.0_3.0_1727253478934.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_scholarbert_pipeline_en_5.5.0_3.0_1727253478934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_scholarbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_scholarbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_scholarbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/globuslabs/ScholarBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-somali_what_en.md b/docs/_posts/ahmedlone127/2024-09-25-somali_what_en.md new file mode 100644 index 00000000000000..1661ca85be59a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-somali_what_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English somali_what BertForSequenceClassification from omarelsayeed +author: John Snow Labs +name: somali_what +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`somali_what` is a English model originally trained by omarelsayeed. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/somali_what_en_5.5.0_3.0_1727304850951.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/somali_what_en_5.5.0_3.0_1727304850951.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("somali_what","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("somali_what", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|somali_what| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|608.8 MB| + +## References + +https://huggingface.co/omarelsayeed/so_what \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-stsb_vn_en.md b/docs/_posts/ahmedlone127/2024-09-25-stsb_vn_en.md new file mode 100644 index 00000000000000..654dd7149d8dac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-stsb_vn_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English stsb_vn BertForSequenceClassification from ntrnghia +author: John Snow Labs +name: stsb_vn +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stsb_vn` is a English model originally trained by ntrnghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stsb_vn_en_5.5.0_3.0_1727266063353.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stsb_vn_en_5.5.0_3.0_1727266063353.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("stsb_vn","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("stsb_vn", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|stsb_vn| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/ntrnghia/stsb_vn \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1_en.md b/docs/_posts/ahmedlone127/2024-09-25-symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1_en.md new file mode 100644 index 00000000000000..002fb2961e7585 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1 BertForSequenceClassification from ajtamayoh +author: John Snow Labs +name: symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1` is a English model originally trained by ajtamayoh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1_en_5.5.0_3.0_1727261082271.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1_en_5.5.0_3.0_1727261082271.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("symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|symptoms_tonga_tonga_islands_diagnosis_sonatafyai_bert_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/ajtamayoh/Symptoms_to_Diagnosis_SonatafyAI_BERT_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-test_hub_push_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-test_hub_push_pipeline_en.md new file mode 100644 index 00000000000000..3f5bb90fea2624 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-test_hub_push_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English test_hub_push_pipeline pipeline BertForSequenceClassification from Tonita +author: John Snow Labs +name: test_hub_push_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_hub_push_pipeline` is a English model originally trained by Tonita. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_hub_push_pipeline_en_5.5.0_3.0_1727287939615.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_hub_push_pipeline_en_5.5.0_3.0_1727287939615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("test_hub_push_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("test_hub_push_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_hub_push_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Tonita/test-hub-push + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-test_trainer_alerams_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-test_trainer_alerams_pipeline_en.md new file mode 100644 index 00000000000000..4be55c9cf604c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-test_trainer_alerams_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English test_trainer_alerams_pipeline pipeline BertForSequenceClassification from AleRams +author: John Snow Labs +name: test_trainer_alerams_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_trainer_alerams_pipeline` is a English model originally trained by AleRams. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_alerams_pipeline_en_5.5.0_3.0_1727289733457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_alerams_pipeline_en_5.5.0_3.0_1727289733457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("test_trainer_alerams_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("test_trainer_alerams_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_trainer_alerams_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/AleRams/test-trainer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-text_classification_medical_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-text_classification_medical_pipeline_en.md new file mode 100644 index 00000000000000..952c396e09ffb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-text_classification_medical_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English text_classification_medical_pipeline pipeline BertForSequenceClassification from felipe-nextly +author: John Snow Labs +name: text_classification_medical_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_medical_pipeline` is a English model originally trained by felipe-nextly. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_medical_pipeline_en_5.5.0_3.0_1727295708121.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_medical_pipeline_en_5.5.0_3.0_1727295708121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("text_classification_medical_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("text_classification_medical_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|text_classification_medical_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/felipe-nextly/text-classification-medical + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-tos_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-tos_bert_pipeline_en.md new file mode 100644 index 00000000000000..b0e56951d2012f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-tos_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tos_bert_pipeline pipeline BertForSequenceClassification from prasannadhungana8848 +author: John Snow Labs +name: tos_bert_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tos_bert_pipeline` is a English model originally trained by prasannadhungana8848. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tos_bert_pipeline_en_5.5.0_3.0_1727257656552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tos_bert_pipeline_en_5.5.0_3.0_1727257656552.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tos_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tos_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tos_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/prasannadhungana8848/TOS_BERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-toxic_hubert_hu.md b/docs/_posts/ahmedlone127/2024-09-25-toxic_hubert_hu.md new file mode 100644 index 00000000000000..c01173ab369fac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-toxic_hubert_hu.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Hungarian toxic_hubert BertForSequenceClassification from RabidUmarell +author: John Snow Labs +name: toxic_hubert +date: 2024-09-25 +tags: [hu, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: hu +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxic_hubert` is a Hungarian model originally trained by RabidUmarell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxic_hubert_hu_5.5.0_3.0_1727300468859.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxic_hubert_hu_5.5.0_3.0_1727300468859.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("toxic_hubert","hu") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("toxic_hubert", "hu") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|toxic_hubert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|hu| +|Size:|414.7 MB| + +## References + +https://huggingface.co/RabidUmarell/toxic-hubert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-trac2020_all_a_bert_base_multilingual_uncased_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-25-trac2020_all_a_bert_base_multilingual_uncased_pipeline_xx.md new file mode 100644 index 00000000000000..e4c9a82f3083ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-trac2020_all_a_bert_base_multilingual_uncased_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual trac2020_all_a_bert_base_multilingual_uncased_pipeline pipeline BertForSequenceClassification from socialmediaie +author: John Snow Labs +name: trac2020_all_a_bert_base_multilingual_uncased_pipeline +date: 2024-09-25 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trac2020_all_a_bert_base_multilingual_uncased_pipeline` is a Multilingual model originally trained by socialmediaie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trac2020_all_a_bert_base_multilingual_uncased_pipeline_xx_5.5.0_3.0_1727305695086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trac2020_all_a_bert_base_multilingual_uncased_pipeline_xx_5.5.0_3.0_1727305695086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("trac2020_all_a_bert_base_multilingual_uncased_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("trac2020_all_a_bert_base_multilingual_uncased_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|trac2020_all_a_bert_base_multilingual_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/socialmediaie/TRAC2020_ALL_A_bert-base-multilingual-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline_en.md new file mode 100644 index 00000000000000..3225f8fd418163 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline pipeline BertForSequenceClassification from FpOliveira +author: John Snow Labs +name: tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline` is a English model originally trained by FpOliveira. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline_en_5.5.0_3.0_1727263779864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline_en_5.5.0_3.0_1727263779864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tupi_bert_base_portuguese_cased_multiclass_multilabel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/FpOliveira/tupi-bert-base-portuguese-cased-multiclass-multilabel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-tupy_bert_base_binary_classifier_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-25-tupy_bert_base_binary_classifier_pipeline_pt.md new file mode 100644 index 00000000000000..f4b00dc4e7884b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-tupy_bert_base_binary_classifier_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese tupy_bert_base_binary_classifier_pipeline pipeline BertForSequenceClassification from Silly-Machine +author: John Snow Labs +name: tupy_bert_base_binary_classifier_pipeline +date: 2024-09-25 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tupy_bert_base_binary_classifier_pipeline` is a Portuguese model originally trained by Silly-Machine. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tupy_bert_base_binary_classifier_pipeline_pt_5.5.0_3.0_1727268836545.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tupy_bert_base_binary_classifier_pipeline_pt_5.5.0_3.0_1727268836545.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tupy_bert_base_binary_classifier_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tupy_bert_base_binary_classifier_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tupy_bert_base_binary_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|408.2 MB| + +## References + +https://huggingface.co/Silly-Machine/TuPy-Bert-Base-Binary-Classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-tvcg_entity_classify_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-tvcg_entity_classify_pipeline_en.md new file mode 100644 index 00000000000000..a55c6322735d60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-tvcg_entity_classify_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tvcg_entity_classify_pipeline pipeline BertForSequenceClassification from Yamei +author: John Snow Labs +name: tvcg_entity_classify_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tvcg_entity_classify_pipeline` is a English model originally trained by Yamei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tvcg_entity_classify_pipeline_en_5.5.0_3.0_1727279377240.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tvcg_entity_classify_pipeline_en_5.5.0_3.0_1727279377240.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tvcg_entity_classify_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tvcg_entity_classify_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tvcg_entity_classify_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Yamei/tvcg_entity_classify + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-valueeval24_bert_baseline_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-valueeval24_bert_baseline_english_pipeline_en.md new file mode 100644 index 00000000000000..c45342da842af7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-valueeval24_bert_baseline_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English valueeval24_bert_baseline_english_pipeline pipeline BertForSequenceClassification from JohannesKiesel +author: John Snow Labs +name: valueeval24_bert_baseline_english_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`valueeval24_bert_baseline_english_pipeline` is a English model originally trained by JohannesKiesel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/valueeval24_bert_baseline_english_pipeline_en_5.5.0_3.0_1727284674461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/valueeval24_bert_baseline_english_pipeline_en_5.5.0_3.0_1727284674461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("valueeval24_bert_baseline_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("valueeval24_bert_baseline_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|valueeval24_bert_baseline_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/JohannesKiesel/valueeval24-bert-baseline-en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-vinilm_2021_qa_evaluator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-vinilm_2021_qa_evaluator_pipeline_en.md new file mode 100644 index 00000000000000..3a67cfa2b92605 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-vinilm_2021_qa_evaluator_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English vinilm_2021_qa_evaluator_pipeline pipeline BertForSequenceClassification from VMware +author: John Snow Labs +name: vinilm_2021_qa_evaluator_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vinilm_2021_qa_evaluator_pipeline` is a English model originally trained by VMware. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vinilm_2021_qa_evaluator_pipeline_en_5.5.0_3.0_1727290745417.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vinilm_2021_qa_evaluator_pipeline_en_5.5.0_3.0_1727290745417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("vinilm_2021_qa_evaluator_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("vinilm_2021_qa_evaluator_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vinilm_2021_qa_evaluator_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|250.5 MB| + +## References + +https://huggingface.co/VMware/vinilm-2021-qa-evaluator + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-wb_charcs_extraction_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-wb_charcs_extraction_pipeline_en.md new file mode 100644 index 00000000000000..410353a3c0a6c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-wb_charcs_extraction_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English wb_charcs_extraction_pipeline pipeline BertForTokenClassification from vkimbris +author: John Snow Labs +name: wb_charcs_extraction_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wb_charcs_extraction_pipeline` is a English model originally trained by vkimbris. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wb_charcs_extraction_pipeline_en_5.5.0_3.0_1727272003689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wb_charcs_extraction_pipeline_en_5.5.0_3.0_1727272003689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("wb_charcs_extraction_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("wb_charcs_extraction_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wb_charcs_extraction_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|662.0 MB| + +## References + +https://huggingface.co/vkimbris/wb-charcs-extraction + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-winobias_bert_base_uncased_classifieronly_en.md b/docs/_posts/ahmedlone127/2024-09-25-winobias_bert_base_uncased_classifieronly_en.md new file mode 100644 index 00000000000000..f43de8c6ceecb8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-winobias_bert_base_uncased_classifieronly_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English winobias_bert_base_uncased_classifieronly BertForSequenceClassification from henryscheible +author: John Snow Labs +name: winobias_bert_base_uncased_classifieronly +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`winobias_bert_base_uncased_classifieronly` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/winobias_bert_base_uncased_classifieronly_en_5.5.0_3.0_1727290546439.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/winobias_bert_base_uncased_classifieronly_en_5.5.0_3.0_1727290546439.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("winobias_bert_base_uncased_classifieronly","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("winobias_bert_base_uncased_classifieronly", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|winobias_bert_base_uncased_classifieronly| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/henryscheible/winobias_bert-base-uncased_classifieronly \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_final_vietnam_aug_insert_bert_2_en.md b/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_final_vietnam_aug_insert_bert_2_en.md new file mode 100644 index 00000000000000..e611f9a398e276 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_final_vietnam_aug_insert_bert_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_final_vietnam_aug_insert_bert_2 XlmRoBertaForSequenceClassification from ThuyNT03 +author: John Snow Labs +name: xlm_roberta_base_final_vietnam_aug_insert_bert_2 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_final_vietnam_aug_insert_bert_2` is a English model originally trained by ThuyNT03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_bert_2_en_5.5.0_3.0_1727228709495.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_final_vietnam_aug_insert_bert_2_en_5.5.0_3.0_1727228709495.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 = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_vietnam_aug_insert_bert_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_final_vietnam_aug_insert_bert_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_final_vietnam_aug_insert_bert_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|794.2 MB| + +## References + +https://huggingface.co/ThuyNT03/xlm-roberta-base-Final_VietNam-aug_insert_BERT-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_irumozhi_ta.md b/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_irumozhi_ta.md new file mode 100644 index 00000000000000..aa51b7d08dd4ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_irumozhi_ta.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Tamil xlm_roberta_base_irumozhi XlmRoBertaForSequenceClassification from aryaman +author: John Snow Labs +name: xlm_roberta_base_irumozhi +date: 2024-09-25 +tags: [ta, open_source, onnx, sequence_classification, xlm_roberta] +task: Text Classification +language: ta +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_irumozhi` is a Tamil model originally trained by aryaman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_irumozhi_ta_5.5.0_3.0_1727229233709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_irumozhi_ta_5.5.0_3.0_1727229233709.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 = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_irumozhi","ta") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_irumozhi", "ta") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_irumozhi| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ta| +|Size:|773.9 MB| + +## References + +https://huggingface.co/aryaman/xlm-roberta-base-irumozhi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline_en.md new file mode 100644 index 00000000000000..d4d31f32998b86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline pipeline XlmRoBertaForSequenceClassification from vocabtrimmer +author: John Snow Labs +name: xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline` is a English model originally trained by vocabtrimmer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline_en_5.5.0_3.0_1727228755130.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline_en_5.5.0_3.0_1727228755130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_trimmed_italian_30000_tweet_sentiment_italian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|389.0 MB| + +## References + +https://huggingface.co/vocabtrimmer/xlm-roberta-base-trimmed-it-30000-tweet-sentiment-it + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-yahoo1_en.md b/docs/_posts/ahmedlone127/2024-09-25-yahoo1_en.md new file mode 100644 index 00000000000000..4a842b846382ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-yahoo1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English yahoo1 BertForSequenceClassification from Lumos +author: John Snow Labs +name: yahoo1 +date: 2024-09-25 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yahoo1` is a English model originally trained by Lumos. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yahoo1_en_5.5.0_3.0_1727272703805.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yahoo1_en_5.5.0_3.0_1727272703805.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("yahoo1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("yahoo1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yahoo1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Lumos/yahoo1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-25-zidan_model_output_v4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-25-zidan_model_output_v4_pipeline_en.md new file mode 100644 index 00000000000000..833c784ddd24c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-25-zidan_model_output_v4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English zidan_model_output_v4_pipeline pipeline BertForSequenceClassification from ZidanAf +author: John Snow Labs +name: zidan_model_output_v4_pipeline +date: 2024-09-25 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zidan_model_output_v4_pipeline` is a English model originally trained by ZidanAf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zidan_model_output_v4_pipeline_en_5.5.0_3.0_1727268497844.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zidan_model_output_v4_pipeline_en_5.5.0_3.0_1727268497844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("zidan_model_output_v4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("zidan_model_output_v4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|zidan_model_output_v4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.0 MB| + +## References + +https://huggingface.co/ZidanAf/Zidan_model_output_v4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-2d6_1600_en.md b/docs/_posts/ahmedlone127/2024-09-26-2d6_1600_en.md new file mode 100644 index 00000000000000..261fc4b1c2795d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-2d6_1600_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English 2d6_1600 BertForSequenceClassification from abbassix +author: John Snow Labs +name: 2d6_1600 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2d6_1600` is a English model originally trained by abbassix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2d6_1600_en_5.5.0_3.0_1727341281407.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2d6_1600_en_5.5.0_3.0_1727341281407.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("2d6_1600","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("2d6_1600", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|2d6_1600| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/abbassix/2d6_1600 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-2d6_800_en.md b/docs/_posts/ahmedlone127/2024-09-26-2d6_800_en.md new file mode 100644 index 00000000000000..b0e95955f36bb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-2d6_800_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English 2d6_800 BertForSequenceClassification from abbassix +author: John Snow Labs +name: 2d6_800 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2d6_800` is a English model originally trained by abbassix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2d6_800_en_5.5.0_3.0_1727382994494.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2d6_800_en_5.5.0_3.0_1727382994494.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("2d6_800","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("2d6_800", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|2d6_800| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/abbassix/2d6_800 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-2d6_800_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-2d6_800_pipeline_en.md new file mode 100644 index 00000000000000..1b76a6a04249c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-2d6_800_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English 2d6_800_pipeline pipeline BertForSequenceClassification from abbassix +author: John Snow Labs +name: 2d6_800_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`2d6_800_pipeline` is a English model originally trained by abbassix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/2d6_800_pipeline_en_5.5.0_3.0_1727383016190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/2d6_800_pipeline_en_5.5.0_3.0_1727383016190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("2d6_800_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("2d6_800_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|2d6_800_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/abbassix/2d6_800 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-absabert_keluhanpln_v5_pipeline_id.md b/docs/_posts/ahmedlone127/2024-09-26-absabert_keluhanpln_v5_pipeline_id.md new file mode 100644 index 00000000000000..01007df600c98f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-absabert_keluhanpln_v5_pipeline_id.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Indonesian absabert_keluhanpln_v5_pipeline pipeline BertForSequenceClassification from radityapranata +author: John Snow Labs +name: absabert_keluhanpln_v5_pipeline +date: 2024-09-26 +tags: [id, open_source, pipeline, onnx] +task: Text Classification +language: id +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`absabert_keluhanpln_v5_pipeline` is a Indonesian model originally trained by radityapranata. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/absabert_keluhanpln_v5_pipeline_id_5.5.0_3.0_1727361826815.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/absabert_keluhanpln_v5_pipeline_id_5.5.0_3.0_1727361826815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("absabert_keluhanpln_v5_pipeline", lang = "id") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("absabert_keluhanpln_v5_pipeline", lang = "id") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|absabert_keluhanpln_v5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|id| +|Size:|409.4 MB| + +## References + +https://huggingface.co/radityapranata/absabert-keluhanpln-v5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-ad_kd_bert_base_uncased_qnli_en.md b/docs/_posts/ahmedlone127/2024-09-26-ad_kd_bert_base_uncased_qnli_en.md new file mode 100644 index 00000000000000..813c2c71584f95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-ad_kd_bert_base_uncased_qnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ad_kd_bert_base_uncased_qnli BertForSequenceClassification from Brucewsy +author: John Snow Labs +name: ad_kd_bert_base_uncased_qnli +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ad_kd_bert_base_uncased_qnli` is a English model originally trained by Brucewsy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ad_kd_bert_base_uncased_qnli_en_5.5.0_3.0_1727381833640.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ad_kd_bert_base_uncased_qnli_en_5.5.0_3.0_1727381833640.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("ad_kd_bert_base_uncased_qnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ad_kd_bert_base_uncased_qnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ad_kd_bert_base_uncased_qnli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Brucewsy/AD-KD_bert_base_uncased_qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-ag_bert_base_uncased_sentence_similarity_v1_en.md b/docs/_posts/ahmedlone127/2024-09-26-ag_bert_base_uncased_sentence_similarity_v1_en.md new file mode 100644 index 00000000000000..d0e28434fe3552 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-ag_bert_base_uncased_sentence_similarity_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ag_bert_base_uncased_sentence_similarity_v1 BertForSequenceClassification from abbasgolestani +author: John Snow Labs +name: ag_bert_base_uncased_sentence_similarity_v1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_bert_base_uncased_sentence_similarity_v1` is a English model originally trained by abbasgolestani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ag_bert_base_uncased_sentence_similarity_v1_en_5.5.0_3.0_1727313741751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ag_bert_base_uncased_sentence_similarity_v1_en_5.5.0_3.0_1727313741751.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("ag_bert_base_uncased_sentence_similarity_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ag_bert_base_uncased_sentence_similarity_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ag_bert_base_uncased_sentence_similarity_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/abbasgolestani/ag-bert-base-uncased-sentence-similarity-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-ag_news_76800_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-26-ag_news_76800_bert_base_uncased_en.md new file mode 100644 index 00000000000000..a28df7510ae9be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-ag_news_76800_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ag_news_76800_bert_base_uncased BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: ag_news_76800_bert_base_uncased +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_76800_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_76800_bert_base_uncased_en_5.5.0_3.0_1727369889899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ag_news_76800_bert_base_uncased_en_5.5.0_3.0_1727369889899.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("ag_news_76800_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ag_news_76800_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ag_news_76800_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/ag-news-76800-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-ag_news_76800_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-ag_news_76800_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..de3150ff485ac4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-ag_news_76800_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ag_news_76800_bert_base_uncased_pipeline pipeline BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: ag_news_76800_bert_base_uncased_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ag_news_76800_bert_base_uncased_pipeline` is a English model originally trained by Kyle1668. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ag_news_76800_bert_base_uncased_pipeline_en_5.5.0_3.0_1727369911505.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ag_news_76800_bert_base_uncased_pipeline_en_5.5.0_3.0_1727369911505.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ag_news_76800_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ag_news_76800_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ag_news_76800_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/ag-news-76800-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-agri_flow_classifier_rjai_bert_en.md b/docs/_posts/ahmedlone127/2024-09-26-agri_flow_classifier_rjai_bert_en.md new file mode 100644 index 00000000000000..448491cf42be2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-agri_flow_classifier_rjai_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English agri_flow_classifier_rjai_bert BertForSequenceClassification from rachitavya +author: John Snow Labs +name: agri_flow_classifier_rjai_bert +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`agri_flow_classifier_rjai_bert` is a English model originally trained by rachitavya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/agri_flow_classifier_rjai_bert_en_5.5.0_3.0_1727378088779.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/agri_flow_classifier_rjai_bert_en_5.5.0_3.0_1727378088779.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("agri_flow_classifier_rjai_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("agri_flow_classifier_rjai_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|agri_flow_classifier_rjai_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rachitavya/agri_flow_classifier_rjai_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-agri_flow_classifier_rjai_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-agri_flow_classifier_rjai_bert_pipeline_en.md new file mode 100644 index 00000000000000..e5bd48f344ad74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-agri_flow_classifier_rjai_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English agri_flow_classifier_rjai_bert_pipeline pipeline BertForSequenceClassification from rachitavya +author: John Snow Labs +name: agri_flow_classifier_rjai_bert_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`agri_flow_classifier_rjai_bert_pipeline` is a English model originally trained by rachitavya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/agri_flow_classifier_rjai_bert_pipeline_en_5.5.0_3.0_1727378111396.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/agri_flow_classifier_rjai_bert_pipeline_en_5.5.0_3.0_1727378111396.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("agri_flow_classifier_rjai_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("agri_flow_classifier_rjai_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|agri_flow_classifier_rjai_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rachitavya/agri_flow_classifier_rjai_bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-albert_base_chinese_finetuned_qqp_en.md b/docs/_posts/ahmedlone127/2024-09-26-albert_base_chinese_finetuned_qqp_en.md new file mode 100644 index 00000000000000..e95bd01178f8e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-albert_base_chinese_finetuned_qqp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_base_chinese_finetuned_qqp BertForSequenceClassification from r10521708 +author: John Snow Labs +name: albert_base_chinese_finetuned_qqp +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_chinese_finetuned_qqp` is a English model originally trained by r10521708. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_chinese_finetuned_qqp_en_5.5.0_3.0_1727391940841.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_chinese_finetuned_qqp_en_5.5.0_3.0_1727391940841.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("albert_base_chinese_finetuned_qqp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("albert_base_chinese_finetuned_qqp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_chinese_finetuned_qqp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|39.8 MB| + +## References + +https://huggingface.co/r10521708/albert-base-chinese-finetuned-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-albert_base_finetuned_chnsenticorp_chinese_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-26-albert_base_finetuned_chnsenticorp_chinese_pipeline_zh.md new file mode 100644 index 00000000000000..890c1051a47d83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-albert_base_finetuned_chnsenticorp_chinese_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese albert_base_finetuned_chnsenticorp_chinese_pipeline pipeline BertForSequenceClassification from WangA +author: John Snow Labs +name: albert_base_finetuned_chnsenticorp_chinese_pipeline +date: 2024-09-26 +tags: [zh, open_source, pipeline, onnx] +task: Text Classification +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_finetuned_chnsenticorp_chinese_pipeline` is a Chinese model originally trained by WangA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_finetuned_chnsenticorp_chinese_pipeline_zh_5.5.0_3.0_1727394777141.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_finetuned_chnsenticorp_chinese_pipeline_zh_5.5.0_3.0_1727394777141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_base_finetuned_chnsenticorp_chinese_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_base_finetuned_chnsenticorp_chinese_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_finetuned_chnsenticorp_chinese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|39.7 MB| + +## References + +https://huggingface.co/WangA/albert-base-finetuned-chnsenticorp-chinese + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-albert_base_finetuned_chnsenticorp_chinese_zh.md b/docs/_posts/ahmedlone127/2024-09-26-albert_base_finetuned_chnsenticorp_chinese_zh.md new file mode 100644 index 00000000000000..f8676503f36df5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-albert_base_finetuned_chnsenticorp_chinese_zh.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Chinese albert_base_finetuned_chnsenticorp_chinese BertForSequenceClassification from WangA +author: John Snow Labs +name: albert_base_finetuned_chnsenticorp_chinese +date: 2024-09-26 +tags: [zh, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_finetuned_chnsenticorp_chinese` is a Chinese model originally trained by WangA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_finetuned_chnsenticorp_chinese_zh_5.5.0_3.0_1727394775015.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_finetuned_chnsenticorp_chinese_zh_5.5.0_3.0_1727394775015.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("albert_base_finetuned_chnsenticorp_chinese","zh") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("albert_base_finetuned_chnsenticorp_chinese", "zh") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_finetuned_chnsenticorp_chinese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|zh| +|Size:|39.6 MB| + +## References + +https://huggingface.co/WangA/albert-base-finetuned-chnsenticorp-chinese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-albert_kor_base_finetuned_classfication_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-albert_kor_base_finetuned_classfication_pipeline_en.md new file mode 100644 index 00000000000000..41e6322a936622 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-albert_kor_base_finetuned_classfication_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English albert_kor_base_finetuned_classfication_pipeline pipeline BertForSequenceClassification from smjung +author: John Snow Labs +name: albert_kor_base_finetuned_classfication_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_kor_base_finetuned_classfication_pipeline` is a English model originally trained by smjung. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_kor_base_finetuned_classfication_pipeline_en_5.5.0_3.0_1727366008597.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_kor_base_finetuned_classfication_pipeline_en_5.5.0_3.0_1727366008597.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_kor_base_finetuned_classfication_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_kor_base_finetuned_classfication_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_kor_base_finetuned_classfication_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|49.9 MB| + +## References + +https://huggingface.co/smjung/albert-kor-base-finetuned-classfication + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-albert_kor_base_finetuned_ynat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-albert_kor_base_finetuned_ynat_pipeline_en.md new file mode 100644 index 00000000000000..da43f1eb30f1b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-albert_kor_base_finetuned_ynat_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English albert_kor_base_finetuned_ynat_pipeline pipeline BertForSequenceClassification from smjung +author: John Snow Labs +name: albert_kor_base_finetuned_ynat_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_kor_base_finetuned_ynat_pipeline` is a English model originally trained by smjung. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_kor_base_finetuned_ynat_pipeline_en_5.5.0_3.0_1727366536897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_kor_base_finetuned_ynat_pipeline_en_5.5.0_3.0_1727366536897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_kor_base_finetuned_ynat_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_kor_base_finetuned_ynat_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_kor_base_finetuned_ynat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|49.9 MB| + +## References + +https://huggingface.co/smjung/albert-kor-base-finetuned-ynat + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-arabert_finetuned_text_classification_en.md b/docs/_posts/ahmedlone127/2024-09-26-arabert_finetuned_text_classification_en.md new file mode 100644 index 00000000000000..951112a6ebc788 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-arabert_finetuned_text_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English arabert_finetuned_text_classification BertForSequenceClassification from AmineSa +author: John Snow Labs +name: arabert_finetuned_text_classification +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_finetuned_text_classification` is a English model originally trained by AmineSa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabert_finetuned_text_classification_en_5.5.0_3.0_1727391345403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabert_finetuned_text_classification_en_5.5.0_3.0_1727391345403.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("arabert_finetuned_text_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("arabert_finetuned_text_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabert_finetuned_text_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/AmineSa/AraBert-finetuned-text-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-arabertv2_fully_supervised_arabic_propaganda_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-arabertv2_fully_supervised_arabic_propaganda_pipeline_en.md new file mode 100644 index 00000000000000..7b6c76f2a9e969 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-arabertv2_fully_supervised_arabic_propaganda_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English arabertv2_fully_supervised_arabic_propaganda_pipeline pipeline BertForSequenceClassification from Bmalmotairy +author: John Snow Labs +name: arabertv2_fully_supervised_arabic_propaganda_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabertv2_fully_supervised_arabic_propaganda_pipeline` is a English model originally trained by Bmalmotairy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabertv2_fully_supervised_arabic_propaganda_pipeline_en_5.5.0_3.0_1727316833452.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabertv2_fully_supervised_arabic_propaganda_pipeline_en_5.5.0_3.0_1727316833452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("arabertv2_fully_supervised_arabic_propaganda_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("arabertv2_fully_supervised_arabic_propaganda_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabertv2_fully_supervised_arabic_propaganda_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/Bmalmotairy/arabertv2-fully-supervised-arabic-propaganda + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-arabglossbert_ar.md b/docs/_posts/ahmedlone127/2024-09-26-arabglossbert_ar.md new file mode 100644 index 00000000000000..ed30e2de83071f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-arabglossbert_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic arabglossbert BertForSequenceClassification from SinaLab +author: John Snow Labs +name: arabglossbert +date: 2024-09-26 +tags: [ar, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabglossbert` is a Arabic model originally trained by SinaLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabglossbert_ar_5.5.0_3.0_1727321721355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabglossbert_ar_5.5.0_3.0_1727321721355.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("arabglossbert","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("arabglossbert", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabglossbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|507.3 MB| + +## References + +https://huggingface.co/SinaLab/ArabGlossBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-autonlp_judulberita_32517788_en.md b/docs/_posts/ahmedlone127/2024-09-26-autonlp_judulberita_32517788_en.md new file mode 100644 index 00000000000000..19a4a1962f23f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-autonlp_judulberita_32517788_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autonlp_judulberita_32517788 BertForSequenceClassification from Fauzan +author: John Snow Labs +name: autonlp_judulberita_32517788 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_judulberita_32517788` is a English model originally trained by Fauzan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autonlp_judulberita_32517788_en_5.5.0_3.0_1727372304142.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autonlp_judulberita_32517788_en_5.5.0_3.0_1727372304142.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("autonlp_judulberita_32517788","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autonlp_judulberita_32517788", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autonlp_judulberita_32517788| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/Fauzan/autonlp-judulberita-32517788 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-autonlp_judulberita_32517788_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-autonlp_judulberita_32517788_pipeline_en.md new file mode 100644 index 00000000000000..40328911b1f156 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-autonlp_judulberita_32517788_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autonlp_judulberita_32517788_pipeline pipeline BertForSequenceClassification from Fauzan +author: John Snow Labs +name: autonlp_judulberita_32517788_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autonlp_judulberita_32517788_pipeline` is a English model originally trained by Fauzan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autonlp_judulberita_32517788_pipeline_en_5.5.0_3.0_1727372325913.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autonlp_judulberita_32517788_pipeline_en_5.5.0_3.0_1727372325913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autonlp_judulberita_32517788_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autonlp_judulberita_32517788_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autonlp_judulberita_32517788_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.0 MB| + +## References + +https://huggingface.co/Fauzan/autonlp-judulberita-32517788 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748790_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748790_pipeline_en.md new file mode 100644 index 00000000000000..7180fe71ddc5c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748790_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_bertbase_imdb_1275748790_pipeline pipeline BertForSequenceClassification from sasha +author: John Snow Labs +name: autotrain_bertbase_imdb_1275748790_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_bertbase_imdb_1275748790_pipeline` is a English model originally trained by sasha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748790_pipeline_en_5.5.0_3.0_1727343265549.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748790_pipeline_en_5.5.0_3.0_1727343265549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_bertbase_imdb_1275748790_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_bertbase_imdb_1275748790_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_bertbase_imdb_1275748790_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasha/autotrain-BERTBase-imdb-1275748790 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748794_en.md b/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748794_en.md new file mode 100644 index 00000000000000..81a0b3a7f46b26 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748794_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autotrain_bertbase_imdb_1275748794 BertForSequenceClassification from sasha +author: John Snow Labs +name: autotrain_bertbase_imdb_1275748794 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_bertbase_imdb_1275748794` is a English model originally trained by sasha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748794_en_5.5.0_3.0_1727384051831.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748794_en_5.5.0_3.0_1727384051831.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("autotrain_bertbase_imdb_1275748794","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_bertbase_imdb_1275748794", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_bertbase_imdb_1275748794| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasha/autotrain-BERTBase-imdb-1275748794 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748794_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748794_pipeline_en.md new file mode 100644 index 00000000000000..7abbe31df10168 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-autotrain_bertbase_imdb_1275748794_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_bertbase_imdb_1275748794_pipeline pipeline BertForSequenceClassification from sasha +author: John Snow Labs +name: autotrain_bertbase_imdb_1275748794_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_bertbase_imdb_1275748794_pipeline` is a English model originally trained by sasha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748794_pipeline_en_5.5.0_3.0_1727384074448.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748794_pipeline_en_5.5.0_3.0_1727384074448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_bertbase_imdb_1275748794_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_bertbase_imdb_1275748794_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_bertbase_imdb_1275748794_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasha/autotrain-BERTBase-imdb-1275748794 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-autotrain_luc_comp429_victorian_authorship_classification_52472123759_en.md b/docs/_posts/ahmedlone127/2024-09-26-autotrain_luc_comp429_victorian_authorship_classification_52472123759_en.md new file mode 100644 index 00000000000000..0d1cd97e26d0f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-autotrain_luc_comp429_victorian_authorship_classification_52472123759_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autotrain_luc_comp429_victorian_authorship_classification_52472123759 BertForSequenceClassification from NicholasSynovic +author: John Snow Labs +name: autotrain_luc_comp429_victorian_authorship_classification_52472123759 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_luc_comp429_victorian_authorship_classification_52472123759` is a English model originally trained by NicholasSynovic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_luc_comp429_victorian_authorship_classification_52472123759_en_5.5.0_3.0_1727386462164.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_luc_comp429_victorian_authorship_classification_52472123759_en_5.5.0_3.0_1727386462164.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("autotrain_luc_comp429_victorian_authorship_classification_52472123759","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_luc_comp429_victorian_authorship_classification_52472123759", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_luc_comp429_victorian_authorship_classification_52472123759| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NicholasSynovic/autotrain-luc-comp429-victorian-authorship-classification-52472123759 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline_en.md new file mode 100644 index 00000000000000..48aaa707d965ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline pipeline BertForSequenceClassification from NicholasSynovic +author: John Snow Labs +name: autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline` is a English model originally trained by NicholasSynovic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline_en_5.5.0_3.0_1727386531953.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline_en_5.5.0_3.0_1727386531953.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_luc_comp429_victorian_authorship_classification_52472123759_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NicholasSynovic/autotrain-luc-comp429-victorian-authorship-classification-52472123759 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-baseline_bert_10k_steps_en.md b/docs/_posts/ahmedlone127/2024-09-26-baseline_bert_10k_steps_en.md new file mode 100644 index 00000000000000..2f8a4478bb51a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-baseline_bert_10k_steps_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English baseline_bert_10k_steps BertForSequenceClassification from jordyvl +author: John Snow Labs +name: baseline_bert_10k_steps +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_10k_steps` is a English model originally trained by jordyvl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baseline_bert_10k_steps_en_5.5.0_3.0_1727365712404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baseline_bert_10k_steps_en_5.5.0_3.0_1727365712404.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("baseline_bert_10k_steps","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("baseline_bert_10k_steps", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|baseline_bert_10k_steps| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.9 MB| + +## References + +https://huggingface.co/jordyvl/baseline_BERT_10K_steps \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-baseline_bert_10k_steps_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-baseline_bert_10k_steps_pipeline_en.md new file mode 100644 index 00000000000000..8007925109aa9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-baseline_bert_10k_steps_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English baseline_bert_10k_steps_pipeline pipeline BertForSequenceClassification from jordyvl +author: John Snow Labs +name: baseline_bert_10k_steps_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baseline_bert_10k_steps_pipeline` is a English model originally trained by jordyvl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baseline_bert_10k_steps_pipeline_en_5.5.0_3.0_1727365732920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baseline_bert_10k_steps_pipeline_en_5.5.0_3.0_1727365732920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("baseline_bert_10k_steps_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("baseline_bert_10k_steps_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|baseline_bert_10k_steps_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.9 MB| + +## References + +https://huggingface.co/jordyvl/baseline_BERT_10K_steps + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_43_multilabel_emotion_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_43_multilabel_emotion_detection_pipeline_en.md new file mode 100644 index 00000000000000..42f5bc87177aef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_43_multilabel_emotion_detection_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_43_multilabel_emotion_detection_pipeline pipeline BertForSequenceClassification from borisn70 +author: John Snow Labs +name: bert_43_multilabel_emotion_detection_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_43_multilabel_emotion_detection_pipeline` is a English model originally trained by borisn70. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_43_multilabel_emotion_detection_pipeline_en_5.5.0_3.0_1727370946646.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_43_multilabel_emotion_detection_pipeline_en_5.5.0_3.0_1727370946646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_43_multilabel_emotion_detection_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_43_multilabel_emotion_detection_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_43_multilabel_emotion_detection_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/borisn70/bert-43-multilabel-emotion-detection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_airlines_news_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_airlines_news_en.md new file mode 100644 index 00000000000000..c1fabe7765e142 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_airlines_news_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_airlines_news BertForSequenceClassification from dahe827 +author: John Snow Labs +name: bert_base_airlines_news +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_airlines_news` is a English model originally trained by dahe827. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_airlines_news_en_5.5.0_3.0_1727378694009.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_airlines_news_en_5.5.0_3.0_1727378694009.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_base_airlines_news","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_airlines_news", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_airlines_news| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/dahe827/BERT-base-airlines-news \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_airlines_news_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_airlines_news_pipeline_en.md new file mode 100644 index 00000000000000..f2995a21a513b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_airlines_news_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_airlines_news_pipeline pipeline BertForSequenceClassification from dahe827 +author: John Snow Labs +name: bert_base_airlines_news_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_airlines_news_pipeline` is a English model originally trained by dahe827. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_airlines_news_pipeline_en_5.5.0_3.0_1727378718217.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_airlines_news_pipeline_en_5.5.0_3.0_1727378718217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_airlines_news_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_airlines_news_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_airlines_news_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/dahe827/BERT-base-airlines-news + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabert_nejma6_clf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabert_nejma6_clf_pipeline_en.md new file mode 100644 index 00000000000000..d9a0279e7f3f11 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabert_nejma6_clf_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_arabert_nejma6_clf_pipeline pipeline BertForSequenceClassification from eniafou +author: John Snow Labs +name: bert_base_arabert_nejma6_clf_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabert_nejma6_clf_pipeline` is a English model originally trained by eniafou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabert_nejma6_clf_pipeline_en_5.5.0_3.0_1727372492822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabert_nejma6_clf_pipeline_en_5.5.0_3.0_1727372492822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_arabert_nejma6_clf_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_arabert_nejma6_clf_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabert_nejma6_clf_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/eniafou/bert-base-arabert-nejma6-clf + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabertv2_1_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabertv2_1_en.md new file mode 100644 index 00000000000000..98f928ef86d6c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabertv2_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_arabertv2_1 BertForSequenceClassification from elsayedissa +author: John Snow Labs +name: bert_base_arabertv2_1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_1` is a English model originally trained by elsayedissa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_1_en_5.5.0_3.0_1727346264359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_1_en_5.5.0_3.0_1727346264359.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_base_arabertv2_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv2_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/elsayedissa/bert-base-arabertv2_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_en.md new file mode 100644 index 00000000000000..e18d1458c91d71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2 BertForSequenceClassification from Abdelrahman-Rezk +author: John Snow Labs +name: bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_finetuned_qawaf2` is a English model originally trained by Abdelrahman-Rezk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_en_5.5.0_3.0_1727376361728.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_en_5.5.0_3.0_1727376361728.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_base_arabic_camelbert_mix_poetry_finetuned_qawaf2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/Abdelrahman-Rezk/bert-base-arabic-camelbert-mix-poetry-finetuned-qawaf2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline_en.md new file mode 100644 index 00000000000000..f2ea750439fec8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline pipeline BertForSequenceClassification from Abdelrahman-Rezk +author: John Snow Labs +name: bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline` is a English model originally trained by Abdelrahman-Rezk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline_en_5.5.0_3.0_1727376383298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline_en_5.5.0_3.0_1727376383298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_mix_poetry_finetuned_qawaf2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/Abdelrahman-Rezk/bert-base-arabic-camelbert-mix-poetry-finetuned-qawaf2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pedroplanel_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pedroplanel_en.md new file mode 100644 index 00000000000000..ae2a044f54dc27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pedroplanel_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pedroplanel BertForSequenceClassification from pedroplanel +author: John Snow Labs +name: bert_base_banking77_pedroplanel +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_pedroplanel` is a English model originally trained by pedroplanel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pedroplanel_en_5.5.0_3.0_1727377770826.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pedroplanel_en_5.5.0_3.0_1727377770826.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_base_banking77_pedroplanel","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pedroplanel", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pedroplanel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/pedroplanel/bert-base-banking77 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pedroplanel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pedroplanel_pipeline_en.md new file mode 100644 index 00000000000000..487f6ec2f5e386 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pedroplanel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pedroplanel_pipeline pipeline BertForSequenceClassification from pedroplanel +author: John Snow Labs +name: bert_base_banking77_pedroplanel_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pedroplanel_pipeline` is a English model originally trained by pedroplanel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pedroplanel_pipeline_en_5.5.0_3.0_1727377793007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pedroplanel_pipeline_en_5.5.0_3.0_1727377793007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pedroplanel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pedroplanel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pedroplanel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/pedroplanel/bert-base-banking77 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ggaleano_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ggaleano_pipeline_en.md new file mode 100644 index 00000000000000..f0305f844a4c56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ggaleano_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_ggaleano_pipeline pipeline BertForSequenceClassification from ggaleano +author: John Snow Labs +name: bert_base_banking77_pt2_ggaleano_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_ggaleano_pipeline` is a English model originally trained by ggaleano. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_ggaleano_pipeline_en_5.5.0_3.0_1727376247167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_ggaleano_pipeline_en_5.5.0_3.0_1727376247167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_ggaleano_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_ggaleano_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_ggaleano_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/ggaleano/bert-base-banking77-pt2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ngeg2015_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ngeg2015_en.md new file mode 100644 index 00000000000000..c92f5ea48069f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ngeg2015_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pt2_ngeg2015 BertForSequenceClassification from ngeg2015 +author: John Snow Labs +name: bert_base_banking77_pt2_ngeg2015 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ngeg2015` is a English model originally trained by ngeg2015. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_ngeg2015_en_5.5.0_3.0_1727371296369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_ngeg2015_en_5.5.0_3.0_1727371296369.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_base_banking77_pt2_ngeg2015","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_ngeg2015", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_ngeg2015| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/ngeg2015/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ngeg2015_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ngeg2015_pipeline_en.md new file mode 100644 index 00000000000000..9e27ac31a76acd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_ngeg2015_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_ngeg2015_pipeline pipeline BertForSequenceClassification from ngeg2015 +author: John Snow Labs +name: bert_base_banking77_pt2_ngeg2015_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_ngeg2015_pipeline` is a English model originally trained by ngeg2015. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_ngeg2015_pipeline_en_5.5.0_3.0_1727371318190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_ngeg2015_pipeline_en_5.5.0_3.0_1727371318190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_ngeg2015_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_ngeg2015_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_ngeg2015_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/ngeg2015/bert-base-banking77-pt2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_sajjadamjad_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_sajjadamjad_en.md new file mode 100644 index 00000000000000..2c94c19d11d95b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_sajjadamjad_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pt2_sajjadamjad BertForSequenceClassification from sajjadamjad +author: John Snow Labs +name: bert_base_banking77_pt2_sajjadamjad +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sajjadamjad` is a English model originally trained by sajjadamjad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_sajjadamjad_en_5.5.0_3.0_1727339669679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_sajjadamjad_en_5.5.0_3.0_1727339669679.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_base_banking77_pt2_sajjadamjad","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_sajjadamjad", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_sajjadamjad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/sajjadamjad/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_vvuri_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_vvuri_en.md new file mode 100644 index 00000000000000..90151516f99ba6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_pt2_vvuri_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pt2_vvuri BertForSequenceClassification from vvuri +author: John Snow Labs +name: bert_base_banking77_pt2_vvuri +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_vvuri` is a English model originally trained by vvuri. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_vvuri_en_5.5.0_3.0_1727310949017.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_vvuri_en_5.5.0_3.0_1727310949017.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_base_banking77_pt2_vvuri","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_vvuri", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_vvuri| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/vvuri/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_serdarmuhammet_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_serdarmuhammet_en.md new file mode 100644 index 00000000000000..0258b0dab75701 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_serdarmuhammet_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_serdarmuhammet BertForSequenceClassification from Serdarmuhammet +author: John Snow Labs +name: bert_base_banking77_serdarmuhammet +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_serdarmuhammet` is a English model originally trained by Serdarmuhammet. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_serdarmuhammet_en_5.5.0_3.0_1727385198941.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_serdarmuhammet_en_5.5.0_3.0_1727385198941.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_base_banking77_serdarmuhammet","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_serdarmuhammet", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_serdarmuhammet| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Serdarmuhammet/bert-base-banking77 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_serdarmuhammet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_serdarmuhammet_pipeline_en.md new file mode 100644 index 00000000000000..5d1737e7847d6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_banking77_serdarmuhammet_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_serdarmuhammet_pipeline pipeline BertForSequenceClassification from Serdarmuhammet +author: John Snow Labs +name: bert_base_banking77_serdarmuhammet_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_serdarmuhammet_pipeline` is a English model originally trained by Serdarmuhammet. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_serdarmuhammet_pipeline_en_5.5.0_3.0_1727385220506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_serdarmuhammet_pipeline_en_5.5.0_3.0_1727385220506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_serdarmuhammet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_serdarmuhammet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_serdarmuhammet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Serdarmuhammet/bert-base-banking77 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_case_yelp5_tuned_experiment_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_case_yelp5_tuned_experiment_en.md new file mode 100644 index 00000000000000..028007bb6068e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_case_yelp5_tuned_experiment_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_case_yelp5_tuned_experiment BertForSequenceClassification from csabakecskemeti +author: John Snow Labs +name: bert_base_case_yelp5_tuned_experiment +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_case_yelp5_tuned_experiment` is a English model originally trained by csabakecskemeti. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_case_yelp5_tuned_experiment_en_5.5.0_3.0_1727388140452.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_case_yelp5_tuned_experiment_en_5.5.0_3.0_1727388140452.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_base_case_yelp5_tuned_experiment","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_case_yelp5_tuned_experiment", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_case_yelp5_tuned_experiment| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.8 MB| + +## References + +https://huggingface.co/csabakecskemeti/bert-base-case-yelp5-tuned-experiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_en.md new file mode 100644 index 00000000000000..e53a616f9c53cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep BertForSequenceClassification from AbhishekkV19 +author: John Snow Labs +name: bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_5kvul_10aug_3nsfw_10w_exp_10ep` is a English model originally trained by AbhishekkV19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_en_5.5.0_3.0_1727386995122.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_en_5.5.0_3.0_1727386995122.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_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/AbhishekkV19/bert-base-cased-5kvul-10aug-3nsfw-10w-exp-10ep \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline_en.md new file mode 100644 index 00000000000000..3dfa1d4d5142bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline pipeline BertForSequenceClassification from AbhishekkV19 +author: John Snow Labs +name: bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline` is a English model originally trained by AbhishekkV19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline_en_5.5.0_3.0_1727387018791.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline_en_5.5.0_3.0_1727387018791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_5kvul_10aug_3nsfw_10w_exp_10ep_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/AbhishekkV19/bert-base-cased-5kvul-10aug-3nsfw-10w-exp-10ep + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_embed_mixup_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_embed_mixup_pipeline_en.md new file mode 100644 index 00000000000000..6b39f67abfba36 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_embed_mixup_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_embed_mixup_pipeline pipeline BertForSequenceClassification from pa-shk +author: John Snow Labs +name: bert_base_cased_embed_mixup_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_embed_mixup_pipeline` is a English model originally trained by pa-shk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_embed_mixup_pipeline_en_5.5.0_3.0_1727344089546.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_embed_mixup_pipeline_en_5.5.0_3.0_1727344089546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_embed_mixup_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_embed_mixup_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_embed_mixup_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/pa-shk/bert-base-cased-embed-mixup + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_english_sentweet_profane_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_english_sentweet_profane_pipeline_en.md new file mode 100644 index 00000000000000..1eedcbb2dfb973 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_english_sentweet_profane_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_english_sentweet_profane_pipeline pipeline BertForSequenceClassification from jayanta +author: John Snow Labs +name: bert_base_cased_english_sentweet_profane_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_english_sentweet_profane_pipeline` is a English model originally trained by jayanta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_english_sentweet_profane_pipeline_en_5.5.0_3.0_1727350267306.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_english_sentweet_profane_pipeline_en_5.5.0_3.0_1727350267306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_english_sentweet_profane_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_english_sentweet_profane_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_english_sentweet_profane_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jayanta/bert-base-cased-english-sentweet-Profane + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_finetune_yelp_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_finetune_yelp_en.md new file mode 100644 index 00000000000000..c8d93c373f8d02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_finetune_yelp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_finetune_yelp BertForSequenceClassification from overman123 +author: John Snow Labs +name: bert_base_cased_finetune_yelp +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_finetune_yelp` is a English model originally trained by overman123. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetune_yelp_en_5.5.0_3.0_1727386003904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetune_yelp_en_5.5.0_3.0_1727386003904.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_base_cased_finetune_yelp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetune_yelp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetune_yelp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.8 MB| + +## References + +https://huggingface.co/overman123/bert-base-cased-finetune-yelp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_finetuned_filtered_0609_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_finetuned_filtered_0609_pipeline_en.md new file mode 100644 index 00000000000000..8052035b42e0b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_finetuned_filtered_0609_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_finetuned_filtered_0609_pipeline pipeline BertForSequenceClassification from YeRyeongLee +author: John Snow Labs +name: bert_base_cased_finetuned_filtered_0609_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_filtered_0609_pipeline` is a English model originally trained by YeRyeongLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_filtered_0609_pipeline_en_5.5.0_3.0_1727321891682.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_filtered_0609_pipeline_en_5.5.0_3.0_1727321891682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_finetuned_filtered_0609_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_finetuned_filtered_0609_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_filtered_0609_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/YeRyeongLee/bert-base-cased-finetuned-filtered-0609 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_ft6_3ep_s42_toplessonly_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_ft6_3ep_s42_toplessonly_en.md new file mode 100644 index 00000000000000..4d8cf87d6d916b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_ft6_3ep_s42_toplessonly_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_ft6_3ep_s42_toplessonly BertForSequenceClassification from AbhishekkV19 +author: John Snow Labs +name: bert_base_cased_ft6_3ep_s42_toplessonly +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ft6_3ep_s42_toplessonly` is a English model originally trained by AbhishekkV19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft6_3ep_s42_toplessonly_en_5.5.0_3.0_1727323847954.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft6_3ep_s42_toplessonly_en_5.5.0_3.0_1727323847954.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_base_cased_ft6_3ep_s42_toplessonly","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_ft6_3ep_s42_toplessonly", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_ft6_3ep_s42_toplessonly| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/AbhishekkV19/bert-base-cased-ft6-3ep-s42-toplessonly \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_greecewildfire_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_greecewildfire_pipeline_en.md new file mode 100644 index 00000000000000..4061ee11f3f96f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_greecewildfire_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_greecewildfire_pipeline pipeline BertForSequenceClassification from rizvi-rahil786 +author: John Snow Labs +name: bert_base_cased_greecewildfire_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_greecewildfire_pipeline` is a English model originally trained by rizvi-rahil786. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_greecewildfire_pipeline_en_5.5.0_3.0_1727319619086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_greecewildfire_pipeline_en_5.5.0_3.0_1727319619086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_greecewildfire_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_greecewildfire_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_greecewildfire_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/rizvi-rahil786/bert-base-cased-greeceWildfire + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_hatexplain_random_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_hatexplain_random_en.md new file mode 100644 index 00000000000000..1607e1ad2f4ccf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_hatexplain_random_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_hatexplain_random BertForSequenceClassification from gmihaila +author: John Snow Labs +name: bert_base_cased_hatexplain_random +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_hatexplain_random` is a English model originally trained by gmihaila. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_hatexplain_random_en_5.5.0_3.0_1727317614373.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_hatexplain_random_en_5.5.0_3.0_1727317614373.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_base_cased_hatexplain_random","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_hatexplain_random", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_hatexplain_random| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/gmihaila/bert-base-cased-hatexplain-random \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_k1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_k1_pipeline_en.md new file mode 100644 index 00000000000000..bab2049696f961 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_k1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_k1_pipeline pipeline BertForSequenceClassification from dtorber +author: John Snow Labs +name: bert_base_cased_k1_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_k1_pipeline` is a English model originally trained by dtorber. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_k1_pipeline_en_5.5.0_3.0_1727380204997.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_k1_pipeline_en_5.5.0_3.0_1727380204997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_k1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_k1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_k1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/dtorber/bert-base-cased_K1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_last500_sep_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_last500_sep_en.md new file mode 100644 index 00000000000000..1f4417279a098b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_last500_sep_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_last500_sep BertForSequenceClassification from Raychanan +author: John Snow Labs +name: bert_base_cased_last500_sep +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_last500_sep` is a English model originally trained by Raychanan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_last500_sep_en_5.5.0_3.0_1727373511124.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_last500_sep_en_5.5.0_3.0_1727373511124.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_base_cased_last500_sep","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_last500_sep", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_last500_sep| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Raychanan/bert-base-cased-last500-SEP \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_last500_sep_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_last500_sep_pipeline_en.md new file mode 100644 index 00000000000000..bfe5ddf0cea23e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_last500_sep_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_last500_sep_pipeline pipeline BertForSequenceClassification from Raychanan +author: John Snow Labs +name: bert_base_cased_last500_sep_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_last500_sep_pipeline` is a English model originally trained by Raychanan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_last500_sep_pipeline_en_5.5.0_3.0_1727373532561.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_last500_sep_pipeline_en_5.5.0_3.0_1727373532561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_last500_sep_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_last500_sep_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_last500_sep_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Raychanan/bert-base-cased-last500-SEP + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_mlm_chemistry_textcls_rheology_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_mlm_chemistry_textcls_rheology_en.md new file mode 100644 index 00000000000000..9bdbd0b35b72c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_mlm_chemistry_textcls_rheology_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_mlm_chemistry_textcls_rheology BertForSequenceClassification from jonas-luehrs +author: John Snow Labs +name: bert_base_cased_mlm_chemistry_textcls_rheology +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mlm_chemistry_textcls_rheology` is a English model originally trained by jonas-luehrs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_mlm_chemistry_textcls_rheology_en_5.5.0_3.0_1727385108146.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_mlm_chemistry_textcls_rheology_en_5.5.0_3.0_1727385108146.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_base_cased_mlm_chemistry_textcls_rheology","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_mlm_chemistry_textcls_rheology", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_mlm_chemistry_textcls_rheology| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jonas-luehrs/bert-base-cased-MLM-chemistry-textCLS-RHEOLOGY \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_paraphrase_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_paraphrase_classification_pipeline_en.md new file mode 100644 index 00000000000000..6501d335935e27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_paraphrase_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_paraphrase_classification_pipeline pipeline BertForSequenceClassification from rushilJariwala +author: John Snow Labs +name: bert_base_cased_paraphrase_classification_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_paraphrase_classification_pipeline` is a English model originally trained by rushilJariwala. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_paraphrase_classification_pipeline_en_5.5.0_3.0_1727317917833.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_paraphrase_classification_pipeline_en_5.5.0_3.0_1727317917833.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_paraphrase_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_paraphrase_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_paraphrase_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rushilJariwala/bert-base-cased-paraphrase-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_semantics_cls_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_semantics_cls_en.md new file mode 100644 index 00000000000000..f92776783cba84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_semantics_cls_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_semantics_cls BertForSequenceClassification from eunjin +author: John Snow Labs +name: bert_base_cased_semantics_cls +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_semantics_cls` is a English model originally trained by eunjin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_semantics_cls_en_5.5.0_3.0_1727381864535.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_semantics_cls_en_5.5.0_3.0_1727381864535.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_base_cased_semantics_cls","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_semantics_cls", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_semantics_cls| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/eunjin/bert_base_cased_semantics_cls \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_semantics_cls_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_semantics_cls_pipeline_en.md new file mode 100644 index 00000000000000..919d0e5effabc2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_semantics_cls_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_semantics_cls_pipeline pipeline BertForSequenceClassification from eunjin +author: John Snow Labs +name: bert_base_cased_semantics_cls_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_semantics_cls_pipeline` is a English model originally trained by eunjin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_semantics_cls_pipeline_en_5.5.0_3.0_1727381893443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_semantics_cls_pipeline_en_5.5.0_3.0_1727381893443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_semantics_cls_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_semantics_cls_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_semantics_cls_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/eunjin/bert_base_cased_semantics_cls + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_snli_model4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_snli_model4_pipeline_en.md new file mode 100644 index 00000000000000..dcef0b2d3e8bc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_snli_model4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_snli_model4_pipeline pipeline BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_snli_model4_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_snli_model4_pipeline` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model4_pipeline_en_5.5.0_3.0_1727345315777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model4_pipeline_en_5.5.0_3.0_1727345315777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_snli_model4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_snli_model4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_snli_model4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-snli-model4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_snli_model5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_snli_model5_pipeline_en.md new file mode 100644 index 00000000000000..6a8e68a207d8d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_snli_model5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_snli_model5_pipeline pipeline BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_snli_model5_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_snli_model5_pipeline` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model5_pipeline_en_5.5.0_3.0_1727350009860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model5_pipeline_en_5.5.0_3.0_1727350009860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_snli_model5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_snli_model5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_snli_model5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-snli-model5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_temp_classifier_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_temp_classifier_v2_pipeline_en.md new file mode 100644 index 00000000000000..2c15b6367bdcfa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_temp_classifier_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_temp_classifier_v2_pipeline pipeline BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_cased_temp_classifier_v2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_temp_classifier_v2_pipeline` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_temp_classifier_v2_pipeline_en_5.5.0_3.0_1727384590719.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_temp_classifier_v2_pipeline_en_5.5.0_3.0_1727384590719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_temp_classifier_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_temp_classifier_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_temp_classifier_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/research-dump/bert_base_cased_temp_classifier_v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_toxicity_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_toxicity_en.md new file mode 100644 index 00000000000000..932579d070bd98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_toxicity_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_toxicity BertForSequenceClassification from mohsenfayyaz +author: John Snow Labs +name: bert_base_cased_toxicity +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_toxicity` is a English model originally trained by mohsenfayyaz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_toxicity_en_5.5.0_3.0_1727382565312.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_toxicity_en_5.5.0_3.0_1727382565312.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_base_cased_toxicity","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_toxicity", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_toxicity| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/mohsenfayyaz/bert-base-cased-toxicity \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_tweet_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_tweet_sentiment_en.md new file mode 100644 index 00000000000000..0bcf5d33289728 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_tweet_sentiment_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_tweet_sentiment BertForSequenceClassification from prao +author: John Snow Labs +name: bert_base_cased_tweet_sentiment +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_tweet_sentiment` is a English model originally trained by prao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_tweet_sentiment_en_5.5.0_3.0_1727385911323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_tweet_sentiment_en_5.5.0_3.0_1727385911323.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_base_cased_tweet_sentiment","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_tweet_sentiment", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_tweet_sentiment| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/prao/bert-base-cased-tweet-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_tweet_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_tweet_sentiment_pipeline_en.md new file mode 100644 index 00000000000000..2ff5bf8a31abf6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cased_tweet_sentiment_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_tweet_sentiment_pipeline pipeline BertForSequenceClassification from prao +author: John Snow Labs +name: bert_base_cased_tweet_sentiment_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_tweet_sentiment_pipeline` is a English model originally trained by prao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_tweet_sentiment_pipeline_en_5.5.0_3.0_1727385933328.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_tweet_sentiment_pipeline_en_5.5.0_3.0_1727385933328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_tweet_sentiment_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_tweet_sentiment_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_tweet_sentiment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/prao/bert-base-cased-tweet-sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_en.md new file mode 100644 index 00000000000000..355ff0504b20cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab BertForSequenceClassification from Wiebke +author: John Snow Labs +name: bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_casedepoch3_sexist_baseline_with_reddit_and_gab` is a English model originally trained by Wiebke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_en_5.5.0_3.0_1727322986592.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_en_5.5.0_3.0_1727322986592.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_base_casedepoch3_sexist_baseline_with_reddit_and_gab","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Wiebke/bert-base-casedepoch3_sexist_baseline_with_reddit_and_gab \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal_en.md new file mode 100644 index 00000000000000..b47bbf531eb456 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal BertForSequenceClassification from Wiebke +author: John Snow Labs +name: bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_casedepoch3_sexist_baseline_with_reddit_and_gab_equal` is a English model originally trained by Wiebke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal_en_5.5.0_3.0_1727379552485.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal_en_5.5.0_3.0_1727379552485.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_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_casedepoch3_sexist_baseline_with_reddit_and_gab_equal| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Wiebke/bert-base-casedepoch3_sexist_baseline_with_reddit_and_gab_equal \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_accidentreason_classifier_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_accidentreason_classifier_pipeline_zh.md new file mode 100644 index 00000000000000..c1cace26400347 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_accidentreason_classifier_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese bert_base_chinese_accidentreason_classifier_pipeline pipeline BertForSequenceClassification from posie +author: John Snow Labs +name: bert_base_chinese_accidentreason_classifier_pipeline +date: 2024-09-26 +tags: [zh, open_source, pipeline, onnx] +task: Text Classification +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_accidentreason_classifier_pipeline` is a Chinese model originally trained by posie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_accidentreason_classifier_pipeline_zh_5.5.0_3.0_1727369495777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_accidentreason_classifier_pipeline_zh_5.5.0_3.0_1727369495777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_accidentreason_classifier_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_accidentreason_classifier_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_accidentreason_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|382.5 MB| + +## References + +https://huggingface.co/posie/bert-base-chinese-accidentreason-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_2_en.md new file mode 100644 index 00000000000000..3048162b91adb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_related_prediction_2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_related_prediction_2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_related_prediction_2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_2_en_5.5.0_3.0_1727355681349.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_2_en_5.5.0_3.0_1727355681349.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_base_chinese_climate_related_prediction_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_related_prediction_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_related_prediction_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-related-prediction-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_v3_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_v3_en.md new file mode 100644 index 00000000000000..364ec575e57b3a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_v3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_related_prediction_v3 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_related_prediction_v3 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_related_prediction_v3` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_v3_en_5.5.0_3.0_1727378764395.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_v3_en_5.5.0_3.0_1727378764395.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_base_chinese_climate_related_prediction_v3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_related_prediction_v3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_related_prediction_v3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-related-prediction-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_v6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_v6_pipeline_en.md new file mode 100644 index 00000000000000..942235d5333b51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_v6_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_related_prediction_v6_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_related_prediction_v6_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_related_prediction_v6_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_v6_pipeline_en_5.5.0_3.0_1727311688511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_v6_pipeline_en_5.5.0_3.0_1727311688511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_related_prediction_v6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_related_prediction_v6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_related_prediction_v6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-related-prediction-v6 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_vv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_vv2_pipeline_en.md new file mode 100644 index 00000000000000..7834c1e9f9039c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_related_prediction_vv2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_related_prediction_vv2_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_related_prediction_vv2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_related_prediction_vv2_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_vv2_pipeline_en_5.5.0_3.0_1727383749208.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_vv2_pipeline_en_5.5.0_3.0_1727383749208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_related_prediction_vv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_related_prediction_vv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_related_prediction_vv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-related-prediction-vv2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_3_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_3_en.md new file mode 100644 index 00000000000000..67ccda429ed853 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_3 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_3 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_risk_opportunity_prediction_3` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_3_en_5.5.0_3.0_1727384191797.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_3_en_5.5.0_3.0_1727384191797.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_base_chinese_climate_risk_opportunity_prediction_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_risk_opportunity_prediction_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline_en.md new file mode 100644 index 00000000000000..f43d27c4101b5d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline_en_5.5.0_3.0_1727384214057.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline_en_5.5.0_3.0_1727384214057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_5_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_5_en.md new file mode 100644 index 00000000000000..6fbfff3c5305c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_5 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_5 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_risk_opportunity_prediction_5` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_5_en_5.5.0_3.0_1727385404582.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_5_en_5.5.0_3.0_1727385404582.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_base_chinese_climate_risk_opportunity_prediction_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_risk_opportunity_prediction_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline_en.md new file mode 100644 index 00000000000000..5c518f6d885a72 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline_en_5.5.0_3.0_1727385431043.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline_en_5.5.0_3.0_1727385431043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv1_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv1_en.md new file mode 100644 index 00000000000000..b2e54926a61e8f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_vv1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_vv1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_risk_opportunity_prediction_vv1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_vv1_en_5.5.0_3.0_1727388336962.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_vv1_en_5.5.0_3.0_1727388336962.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_base_chinese_climate_risk_opportunity_prediction_vv1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_risk_opportunity_prediction_vv1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_vv1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-vv1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv2_en.md new file mode 100644 index 00000000000000..3de00fc1136ded --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_vv2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_vv2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_risk_opportunity_prediction_vv2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_vv2_en_5.5.0_3.0_1727385624495.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_vv2_en_5.5.0_3.0_1727385624495.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_base_chinese_climate_risk_opportunity_prediction_vv2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_risk_opportunity_prediction_vv2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_vv2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-vv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline_en.md new file mode 100644 index 00000000000000..d6a3e1ba998f5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline_en_5.5.0_3.0_1727385644482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline_en_5.5.0_3.0_1727385644482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_vv2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-vv2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_2_en.md new file mode 100644 index 00000000000000..2bbbc5b7a82fd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_transition_physical_risk_prediction_2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_transition_physical_risk_prediction_2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_transition_physical_risk_prediction_2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_2_en_5.5.0_3.0_1727388466195.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_2_en_5.5.0_3.0_1727388466195.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_base_chinese_climate_transition_physical_risk_prediction_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_transition_physical_risk_prediction_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_transition_physical_risk_prediction_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-transition-physical-risk-prediction-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_3_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_3_en.md new file mode 100644 index 00000000000000..372e23b133949c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_transition_physical_risk_prediction_3 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_transition_physical_risk_prediction_3 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_transition_physical_risk_prediction_3` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_3_en_5.5.0_3.0_1727385749240.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_3_en_5.5.0_3.0_1727385749240.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_base_chinese_climate_transition_physical_risk_prediction_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_transition_physical_risk_prediction_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_transition_physical_risk_prediction_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-transition-physical-risk-prediction-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline_en.md new file mode 100644 index 00000000000000..41c61516a18ef9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline_en_5.5.0_3.0_1727385769454.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline_en_5.5.0_3.0_1727385769454.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_transition_physical_risk_prediction_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-transition-physical-risk-prediction-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_5_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_5_en.md new file mode 100644 index 00000000000000..5f2abf08d5bbeb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_climate_transition_physical_risk_prediction_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_transition_physical_risk_prediction_5 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_transition_physical_risk_prediction_5 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_transition_physical_risk_prediction_5` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_5_en_5.5.0_3.0_1727382474695.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_transition_physical_risk_prediction_5_en_5.5.0_3.0_1727382474695.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_base_chinese_climate_transition_physical_risk_prediction_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_transition_physical_risk_prediction_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_transition_physical_risk_prediction_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-transition-physical-risk-prediction-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_covid19_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_covid19_en.md new file mode 100644 index 00000000000000..4f174096a18a02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_covid19_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_covid19 BertForSequenceClassification from yaoyinnan +author: John Snow Labs +name: bert_base_chinese_covid19 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_covid19` is a English model originally trained by yaoyinnan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_covid19_en_5.5.0_3.0_1727340212492.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_covid19_en_5.5.0_3.0_1727340212492.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_base_chinese_covid19","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_covid19", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_covid19| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/yaoyinnan/bert-base-chinese-covid19 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline_en.md new file mode 100644 index 00000000000000..e2fe446c30ced6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline pipeline BertForSequenceClassification from nlp-guild +author: John Snow Labs +name: bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline` is a English model originally trained by nlp-guild. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline_en_5.5.0_3.0_1727365723813.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline_en_5.5.0_3.0_1727365723813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_intent_recognition_biomedical_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/nlp-guild/bert-base-chinese-finetuned-intent_recognition-biomedical + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cola_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cola_en.md new file mode 100644 index 00000000000000..4b87f71e8dd89d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cola_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cola BertForSequenceClassification from Cheng98 +author: John Snow Labs +name: bert_base_cola +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_cola` is a English model originally trained by Cheng98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cola_en_5.5.0_3.0_1727372609257.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cola_en_5.5.0_3.0_1727372609257.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_base_cola","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cola", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cola| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Cheng98/bert-base-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_cola_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cola_pipeline_en.md new file mode 100644 index 00000000000000..f6d98831f22676 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_cola_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cola_pipeline pipeline BertForSequenceClassification from Cheng98 +author: John Snow Labs +name: bert_base_cola_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cola_pipeline` is a English model originally trained by Cheng98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cola_pipeline_en_5.5.0_3.0_1727372630670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cola_pipeline_en_5.5.0_3.0_1727372630670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cola_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cola_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cola_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Cheng98/bert-base-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_combined_large_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_combined_large_en.md new file mode 100644 index 00000000000000..af417477e10fce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_combined_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_combined_large BertForSequenceClassification from asparius +author: John Snow Labs +name: bert_base_combined_large +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_combined_large` is a English model originally trained by asparius. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_combined_large_en_5.5.0_3.0_1727378830181.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_combined_large_en_5.5.0_3.0_1727378830181.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_base_combined_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_combined_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_combined_large| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/asparius/bert-base-combined-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_culinary_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_culinary_en.md new file mode 100644 index 00000000000000..6086cd05c3015f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_culinary_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_culinary BertForSequenceClassification from juancavallotti +author: John Snow Labs +name: bert_base_culinary +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_culinary` is a English model originally trained by juancavallotti. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_culinary_en_5.5.0_3.0_1727379674708.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_culinary_en_5.5.0_3.0_1727379674708.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_base_culinary","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_culinary", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_culinary| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.1 MB| + +## References + +https://huggingface.co/juancavallotti/bert-base-culinary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_culinary_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_culinary_pipeline_en.md new file mode 100644 index 00000000000000..b739ad35191867 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_culinary_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_culinary_pipeline pipeline BertForSequenceClassification from juancavallotti +author: John Snow Labs +name: bert_base_culinary_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_culinary_pipeline` is a English model originally trained by juancavallotti. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_culinary_pipeline_en_5.5.0_3.0_1727379701932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_culinary_pipeline_en_5.5.0_3.0_1727379701932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_culinary_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_culinary_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_culinary_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.2 MB| + +## References + +https://huggingface.co/juancavallotti/bert-base-culinary + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_daichi_support_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_daichi_support_en.md new file mode 100644 index 00000000000000..83a97735372f51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_daichi_support_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_daichi_support BertForSequenceClassification from DonMakar +author: John Snow Labs +name: bert_base_daichi_support +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_daichi_support` is a English model originally trained by DonMakar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_daichi_support_en_5.5.0_3.0_1727346200792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_daichi_support_en_5.5.0_3.0_1727346200792.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_base_daichi_support","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_daichi_support", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_daichi_support| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DonMakar/bert-base-Daichi_support \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_emotion_48_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_emotion_48_en.md new file mode 100644 index 00000000000000..e2ca2146bd52ff --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_emotion_48_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_emotion_48 BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_emotion_48 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_48` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_emotion_48_en_5.5.0_3.0_1727388173602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_emotion_48_en_5.5.0_3.0_1727388173602.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_base_emotion_48","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_emotion_48", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_emotion_48| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.2 MB| + +## References + +https://huggingface.co/gokuls/bert-base-emotion_48 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_emotion_48_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_emotion_48_pipeline_en.md new file mode 100644 index 00000000000000..32c48be0771003 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_emotion_48_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_emotion_48_pipeline pipeline BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_emotion_48_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_emotion_48_pipeline` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_emotion_48_pipeline_en_5.5.0_3.0_1727388196313.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_emotion_48_pipeline_en_5.5.0_3.0_1727388196313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_emotion_48_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_emotion_48_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_emotion_48_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.2 MB| + +## References + +https://huggingface.co/gokuls/bert-base-emotion_48 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_eliza_dukim_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_eliza_dukim_en.md new file mode 100644 index 00000000000000..838f47ffaeb9b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_eliza_dukim_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_finetuned_sts_eliza_dukim BertForSequenceClassification from eliza-dukim +author: John Snow Labs +name: bert_base_finetuned_sts_eliza_dukim +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_eliza_dukim` is a English model originally trained by eliza-dukim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_eliza_dukim_en_5.5.0_3.0_1727371165392.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_eliza_dukim_en_5.5.0_3.0_1727371165392.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_base_finetuned_sts_eliza_dukim","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_sts_eliza_dukim", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_sts_eliza_dukim| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/eliza-dukim/bert-base-finetuned-sts \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_eliza_dukim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_eliza_dukim_pipeline_en.md new file mode 100644 index 00000000000000..d86aad3a06eaad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_eliza_dukim_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_finetuned_sts_eliza_dukim_pipeline pipeline BertForSequenceClassification from eliza-dukim +author: John Snow Labs +name: bert_base_finetuned_sts_eliza_dukim_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_sts_eliza_dukim_pipeline` is a English model originally trained by eliza-dukim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_eliza_dukim_pipeline_en_5.5.0_3.0_1727371187308.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_eliza_dukim_pipeline_en_5.5.0_3.0_1727371187308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_finetuned_sts_eliza_dukim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_finetuned_sts_eliza_dukim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_sts_eliza_dukim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/eliza-dukim/bert-base-finetuned-sts + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_gyeoldere_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_gyeoldere_en.md new file mode 100644 index 00000000000000..77e744dcfa5e7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_sts_gyeoldere_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_finetuned_sts_gyeoldere BertForSequenceClassification from gyeoldere +author: John Snow Labs +name: bert_base_finetuned_sts_gyeoldere +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_gyeoldere` is a English model originally trained by gyeoldere. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_gyeoldere_en_5.5.0_3.0_1727386443443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_gyeoldere_en_5.5.0_3.0_1727386443443.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_base_finetuned_sts_gyeoldere","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_sts_gyeoldere", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_sts_gyeoldere| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/gyeoldere/bert-base-finetuned-sts \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_ynat_kyeul611_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_ynat_kyeul611_en.md new file mode 100644 index 00000000000000..dab324cc2deba7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_ynat_kyeul611_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_finetuned_ynat_kyeul611 BertForSequenceClassification from kyeul611 +author: John Snow Labs +name: bert_base_finetuned_ynat_kyeul611 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_kyeul611` is a English model originally trained by kyeul611. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_kyeul611_en_5.5.0_3.0_1727382311954.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_kyeul611_en_5.5.0_3.0_1727382311954.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_base_finetuned_ynat_kyeul611","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_ynat_kyeul611", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_ynat_kyeul611| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/kyeul611/bert-base-finetuned-ynat \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_ynat_kyeul611_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_ynat_kyeul611_pipeline_en.md new file mode 100644 index 00000000000000..f02eac1a0c00be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_finetuned_ynat_kyeul611_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_finetuned_ynat_kyeul611_pipeline pipeline BertForSequenceClassification from kyeul611 +author: John Snow Labs +name: bert_base_finetuned_ynat_kyeul611_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_ynat_kyeul611_pipeline` is a English model originally trained by kyeul611. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_kyeul611_pipeline_en_5.5.0_3.0_1727382337049.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_kyeul611_pipeline_en_5.5.0_3.0_1727382337049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_finetuned_ynat_kyeul611_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_finetuned_ynat_kyeul611_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_ynat_kyeul611_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/kyeul611/bert-base-finetuned-ynat + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_galician_cased_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_galician_cased_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..35c94196e76ade --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_galician_cased_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_galician_cased_finetuned_pipeline pipeline BertForSequenceClassification from gamallo +author: John Snow Labs +name: bert_base_galician_cased_finetuned_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_galician_cased_finetuned_pipeline` is a English model originally trained by gamallo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_galician_cased_finetuned_pipeline_en_5.5.0_3.0_1727393572792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_galician_cased_finetuned_pipeline_en_5.5.0_3.0_1727393572792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_galician_cased_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_galician_cased_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_galician_cased_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|666.7 MB| + +## References + +https://huggingface.co/gamallo/bert-base-gl-cased-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_german_cased_finetuned_partypredictor_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_german_cased_finetuned_partypredictor_en.md new file mode 100644 index 00000000000000..a33a83f76c14ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_german_cased_finetuned_partypredictor_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_german_cased_finetuned_partypredictor BertForSequenceClassification from threite +author: John Snow Labs +name: bert_base_german_cased_finetuned_partypredictor +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_finetuned_partypredictor` is a English model originally trained by threite. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_finetuned_partypredictor_en_5.5.0_3.0_1727377696649.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_finetuned_partypredictor_en_5.5.0_3.0_1727377696649.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_base_german_cased_finetuned_partypredictor","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_german_cased_finetuned_partypredictor", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_german_cased_finetuned_partypredictor| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.1 MB| + +## References + +https://huggingface.co/threite/bert-base-german-cased-finetuned-partypredictor \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_german_cased_finetuned_partypredictor_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_german_cased_finetuned_partypredictor_pipeline_en.md new file mode 100644 index 00000000000000..ffbc0ddd36c953 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_german_cased_finetuned_partypredictor_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_german_cased_finetuned_partypredictor_pipeline pipeline BertForSequenceClassification from threite +author: John Snow Labs +name: bert_base_german_cased_finetuned_partypredictor_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_finetuned_partypredictor_pipeline` is a English model originally trained by threite. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_finetuned_partypredictor_pipeline_en_5.5.0_3.0_1727377720510.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_finetuned_partypredictor_pipeline_en_5.5.0_3.0_1727377720510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_german_cased_finetuned_partypredictor_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_german_cased_finetuned_partypredictor_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_german_cased_finetuned_partypredictor_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/threite/bert-base-german-cased-finetuned-partypredictor + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma_en.md new file mode 100644 index 00000000000000..3826b96679b323 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma BertForSequenceClassification from rahmaabusalma +author: John Snow Labs +name: bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma` is a English model originally trained by rahmaabusalma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma_en_5.5.0_3.0_1727345159217.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma_en_5.5.0_3.0_1727345159217.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_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_indonesian_1_5g_sentiment_analysis_smsa_tuning_rahmaabusalma| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.8 MB| + +## References + +https://huggingface.co/rahmaabusalma/bert-base-indonesian-1.5G-sentiment-analysis-smsa-tuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_japanese_basic_char_v2_irony_ja.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_japanese_basic_char_v2_irony_ja.md new file mode 100644 index 00000000000000..c535f1388a631f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_japanese_basic_char_v2_irony_ja.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Japanese bert_base_japanese_basic_char_v2_irony BertForSequenceClassification from kit-nlp +author: John Snow Labs +name: bert_base_japanese_basic_char_v2_irony +date: 2024-09-26 +tags: [ja, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ja +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_japanese_basic_char_v2_irony` is a Japanese model originally trained by kit-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_japanese_basic_char_v2_irony_ja_5.5.0_3.0_1727344236984.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_japanese_basic_char_v2_irony_ja_5.5.0_3.0_1727344236984.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_base_japanese_basic_char_v2_irony","ja") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_japanese_basic_char_v2_irony", "ja") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_japanese_basic_char_v2_irony| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ja| +|Size:|339.9 MB| + +## References + +https://huggingface.co/kit-nlp/bert-base-japanese-basic-char-v2-irony \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_malayalam_politics_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_malayalam_politics_en.md new file mode 100644 index 00000000000000..91d2978222e874 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_malayalam_politics_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_malayalam_politics BertForSequenceClassification from kalawinka +author: John Snow Labs +name: bert_base_malayalam_politics +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_malayalam_politics` is a English model originally trained by kalawinka. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_malayalam_politics_en_5.5.0_3.0_1727368827815.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_malayalam_politics_en_5.5.0_3.0_1727368827815.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_base_malayalam_politics","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_malayalam_politics", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_malayalam_politics| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.7 MB| + +## References + +https://huggingface.co/kalawinka/bert-base-ml-politics \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_malayalam_politics_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_malayalam_politics_pipeline_en.md new file mode 100644 index 00000000000000..d8e31ab554b27c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_malayalam_politics_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_malayalam_politics_pipeline pipeline BertForSequenceClassification from kalawinka +author: John Snow Labs +name: bert_base_malayalam_politics_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_malayalam_politics_pipeline` is a English model originally trained by kalawinka. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_malayalam_politics_pipeline_en_5.5.0_3.0_1727368860973.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_malayalam_politics_pipeline_en_5.5.0_3.0_1727368860973.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_malayalam_politics_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_malayalam_politics_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_malayalam_politics_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|627.8 MB| + +## References + +https://huggingface.co/kalawinka/bert-base-ml-politics + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_massive_intent_24_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_massive_intent_24_pipeline_en.md new file mode 100644 index 00000000000000..9cdfa9cd6956c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_massive_intent_24_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_massive_intent_24_pipeline pipeline BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_massive_intent_24_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_massive_intent_24_pipeline` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_massive_intent_24_pipeline_en_5.5.0_3.0_1727318876438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_massive_intent_24_pipeline_en_5.5.0_3.0_1727318876438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_massive_intent_24_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_massive_intent_24_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_massive_intent_24_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-Massive-intent_24 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_mnli_en.md new file mode 100644 index 00000000000000..6879d69b91ee18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_mnli_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English bert_base_mnli BertForSequenceClassification from aloxatel +author: John Snow Labs +name: bert_base_mnli +date: 2024-09-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_mnli_en_5.5.0_3.0_1727386996940.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_mnli_en_5.5.0_3.0_1727386996940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## 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 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +References + +https://huggingface.co/aloxatel/bert-base-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_csfever_nearestp_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_csfever_nearestp_xx.md new file mode 100644 index 00000000000000..086233d5db1847 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_csfever_nearestp_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_csfever_nearestp BertForSequenceClassification from ctu-aic +author: John Snow Labs +name: bert_base_multilingual_cased_csfever_nearestp +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_csfever_nearestp` is a Multilingual model originally trained by ctu-aic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_csfever_nearestp_xx_5.5.0_3.0_1727373724828.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_csfever_nearestp_xx_5.5.0_3.0_1727373724828.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_base_multilingual_cased_csfever_nearestp","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_csfever_nearestp", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_csfever_nearestp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/ctu-aic/bert-base-multilingual-cased-csfever_nearestp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline_xx.md new file mode 100644 index 00000000000000..7d9b03a3f93527 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline pipeline BertForSequenceClassification from Sam12111 +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline` is a Multilingual model originally trained by Sam12111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline_xx_5.5.0_3.0_1727378400241.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline_xx_5.5.0_3.0_1727378400241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Sam12111/bert-base-multilingual-cased-finetuned-MeIA-AlfaSolitarioAnalisis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline_xx.md new file mode 100644 index 00000000000000..ecee33ed03aab5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline pipeline BertForSequenceClassification from Sam12111 +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline` is a Multilingual model originally trained by Sam12111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline_xx_5.5.0_3.0_1727388068244.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline_xx_5.5.0_3.0_1727388068244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Sam12111/bert-base-multilingual-cased-finetuned-MeIA-AlfaSolitarioAnalisisDos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_xx.md new file mode 100644 index 00000000000000..a81ff45454ccec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos BertForSequenceClassification from Sam12111 +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_meia_alfasolitarioanalisisdos` is a Multilingual model originally trained by Sam12111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_xx_5.5.0_3.0_1727388020477.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos_xx_5.5.0_3.0_1727388020477.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_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_meia_alfasolitarioanalisisdos| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Sam12111/bert-base-multilingual-cased-finetuned-MeIA-AlfaSolitarioAnalisisDos \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline_xx.md new file mode 100644 index 00000000000000..c83e03b10e1602 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline pipeline BertForSequenceClassification from hugo1499 +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline` is a Multilingual model originally trained by hugo1499. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline_xx_5.5.0_3.0_1727350786881.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline_xx_5.5.0_3.0_1727350786881.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_meia_analisisdesentimientos_hugo1499_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/hugo1499/bert-base-multilingual-cased-finetuned-MeIA-AnalisisDeSentimientos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_papluca_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_papluca_pipeline_xx.md new file mode 100644 index 00000000000000..72df308d1c248b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_papluca_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_papluca_pipeline pipeline BertForSequenceClassification from CHKIVY +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_papluca_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_papluca_pipeline` is a Multilingual model originally trained by CHKIVY. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_papluca_pipeline_xx_5.5.0_3.0_1727382403263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_papluca_pipeline_xx_5.5.0_3.0_1727382403263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_papluca_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_papluca_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_papluca_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.4 MB| + +## References + +https://huggingface.co/CHKIVY/bert-base-multilingual-cased-finetuned-papluca + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_papluca_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_papluca_xx.md new file mode 100644 index 00000000000000..43f6de06abb777 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuned_papluca_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_papluca BertForSequenceClassification from CHKIVY +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_papluca +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_papluca` is a Multilingual model originally trained by CHKIVY. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_papluca_xx_5.5.0_3.0_1727382359150.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_papluca_xx_5.5.0_3.0_1727382359150.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_base_multilingual_cased_finetuned_papluca","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_finetuned_papluca", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_papluca| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/CHKIVY/bert-base-multilingual-cased-finetuned-papluca \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline_xx.md new file mode 100644 index 00000000000000..3fe44dc8035e5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline pipeline BertForSequenceClassification from seriouspark +author: John Snow Labs +name: bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline` is a Multilingual model originally trained by seriouspark. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline_xx_5.5.0_3.0_1727374966615.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline_xx_5.5.0_3.0_1727374966615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuning_sentimental_6label_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/seriouspark/bert-base-multilingual-cased-finetuning-sentimental-6label + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_impact_term_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_impact_term_xx.md new file mode 100644 index 00000000000000..0688267577341d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_impact_term_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_impact_term BertForSequenceClassification from Tuiaia +author: John Snow Labs +name: bert_base_multilingual_cased_impact_term +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_impact_term` is a Multilingual model originally trained by Tuiaia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_impact_term_xx_5.5.0_3.0_1727380969186.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_impact_term_xx_5.5.0_3.0_1727380969186.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_base_multilingual_cased_impact_term","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_impact_term", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_impact_term| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Tuiaia/bert-base-multilingual-cased-impact-term \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mnli_1_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mnli_1_pipeline_xx.md new file mode 100644 index 00000000000000..893dc02e52a0a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mnli_1_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_mnli_1_pipeline pipeline BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_mnli_1_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_mnli_1_pipeline` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mnli_1_pipeline_xx_5.5.0_3.0_1727380246942.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mnli_1_pipeline_xx_5.5.0_3.0_1727380246942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_mnli_1_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_mnli_1_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_mnli_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-mnli-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mnli_1_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mnli_1_xx.md new file mode 100644 index 00000000000000..8479b3168de71d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mnli_1_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_mnli_1 BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_mnli_1 +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mnli_1` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mnli_1_xx_5.5.0_3.0_1727380204013.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mnli_1_xx_5.5.0_3.0_1727380204013.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_base_multilingual_cased_mnli_1","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_mnli_1", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_mnli_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-mnli-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mrpc_10_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mrpc_10_pipeline_xx.md new file mode 100644 index 00000000000000..7dc536f653a998 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_mrpc_10_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_mrpc_10_pipeline pipeline BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_mrpc_10_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_mrpc_10_pipeline` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mrpc_10_pipeline_xx_5.5.0_3.0_1727319659884.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mrpc_10_pipeline_xx_5.5.0_3.0_1727319659884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_mrpc_10_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_mrpc_10_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_mrpc_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-mrpc-10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_qqp_10_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_qqp_10_pipeline_xx.md new file mode 100644 index 00000000000000..a2db328274362d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_qqp_10_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_qqp_10_pipeline pipeline BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_qqp_10_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_qqp_10_pipeline` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_qqp_10_pipeline_xx_5.5.0_3.0_1727374593227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_qqp_10_pipeline_xx_5.5.0_3.0_1727374593227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_qqp_10_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_qqp_10_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_qqp_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-qqp-10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_qqp_10_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_qqp_10_xx.md new file mode 100644 index 00000000000000..496b07b1d02d16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_qqp_10_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_qqp_10 BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_qqp_10 +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_qqp_10` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_qqp_10_xx_5.5.0_3.0_1727374557944.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_qqp_10_xx_5.5.0_3.0_1727374557944.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_base_multilingual_cased_qqp_10","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_qqp_10", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_qqp_10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-qqp-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_rte_1_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_rte_1_xx.md new file mode 100644 index 00000000000000..2fd910791cb1aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_rte_1_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_rte_1 BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_rte_1 +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_rte_1` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_rte_1_xx_5.5.0_3.0_1727382128642.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_rte_1_xx_5.5.0_3.0_1727382128642.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_base_multilingual_cased_rte_1","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_rte_1", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_rte_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-rte-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline_xx.md new file mode 100644 index 00000000000000..d0d83e40deae20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline pipeline BertForSequenceClassification from PrevenIA +author: John Snow Labs +name: bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline` is a Multilingual model originally trained by PrevenIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline_xx_5.5.0_3.0_1727375078589.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline_xx_5.5.0_3.0_1727375078589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_spanish_suicide_intent_information_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/PrevenIA/bert-base-multilingual-cased-spanish-suicide-intent-information-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_spanish_suicide_intent_information_v2_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_spanish_suicide_intent_information_v2_xx.md new file mode 100644 index 00000000000000..0b90299bb6bfbd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_spanish_suicide_intent_information_v2_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_spanish_suicide_intent_information_v2 BertForSequenceClassification from PrevenIA +author: John Snow Labs +name: bert_base_multilingual_cased_spanish_suicide_intent_information_v2 +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_spanish_suicide_intent_information_v2` is a Multilingual model originally trained by PrevenIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_spanish_suicide_intent_information_v2_xx_5.5.0_3.0_1727375043034.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_spanish_suicide_intent_information_v2_xx_5.5.0_3.0_1727375043034.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_base_multilingual_cased_spanish_suicide_intent_information_v2","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_spanish_suicide_intent_information_v2", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_spanish_suicide_intent_information_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/PrevenIA/bert-base-multilingual-cased-spanish-suicide-intent-information-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_vsmec_10_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_vsmec_10_pipeline_xx.md new file mode 100644 index 00000000000000..be0be5e0c7949d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_vsmec_10_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_vsmec_10_pipeline pipeline BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_vsmec_10_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_vsmec_10_pipeline` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_vsmec_10_pipeline_xx_5.5.0_3.0_1727318440220.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_vsmec_10_pipeline_xx_5.5.0_3.0_1727318440220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_vsmec_10_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_vsmec_10_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_vsmec_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-vsmec-10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_wnli_100_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_wnli_100_pipeline_xx.md new file mode 100644 index 00000000000000..ae89ed94a9be0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_wnli_100_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_wnli_100_pipeline pipeline BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_wnli_100_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_wnli_100_pipeline` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_wnli_100_pipeline_xx_5.5.0_3.0_1727379153410.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_wnli_100_pipeline_xx_5.5.0_3.0_1727379153410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_wnli_100_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_wnli_100_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_wnli_100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-wnli-100 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_wnli_100_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_wnli_100_xx.md new file mode 100644 index 00000000000000..0a77f3f0e902cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_cased_wnli_100_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_wnli_100 BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_wnli_100 +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_wnli_100` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_wnli_100_xx_5.5.0_3.0_1727379113851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_wnli_100_xx_5.5.0_3.0_1727379113851.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_base_multilingual_cased_wnli_100","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_wnli_100", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_wnli_100| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-wnli-100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction_xx.md new file mode 100644 index 00000000000000..ced77d7ca0486c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction BertForSequenceClassification from liy140 +author: John Snow Labs +name: bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_chunk_filter_for_metadata_extraction` is a Multilingual model originally trained by liy140. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction_xx_5.5.0_3.0_1727378270670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction_xx_5.5.0_3.0_1727378270670.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_base_multilingual_uncased_chunk_filter_for_metadata_extraction","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_chunk_filter_for_metadata_extraction| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/liy140/bert-base-multilingual-uncased_chunk_filter_for_metadata_extraction \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_finetuned_solidarity_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_finetuned_solidarity_pipeline_xx.md new file mode 100644 index 00000000000000..7e9463b1ecc866 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_finetuned_solidarity_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_finetuned_solidarity_pipeline pipeline BertForSequenceClassification from amaurits +author: John Snow Labs +name: bert_base_multilingual_uncased_finetuned_solidarity_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_finetuned_solidarity_pipeline` is a Multilingual model originally trained by amaurits. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_finetuned_solidarity_pipeline_xx_5.5.0_3.0_1727382515104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_finetuned_solidarity_pipeline_xx_5.5.0_3.0_1727382515104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_uncased_finetuned_solidarity_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_uncased_finetuned_solidarity_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_finetuned_solidarity_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/amaurits/bert-base-multilingual-uncased-finetuned-solidarity + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_finetuned_solidarity_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_finetuned_solidarity_xx.md new file mode 100644 index 00000000000000..849a3d2e978d7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_finetuned_solidarity_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_finetuned_solidarity BertForSequenceClassification from amaurits +author: John Snow Labs +name: bert_base_multilingual_uncased_finetuned_solidarity +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_solidarity` is a Multilingual model originally trained by amaurits. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_finetuned_solidarity_xx_5.5.0_3.0_1727382478111.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_finetuned_solidarity_xx_5.5.0_3.0_1727382478111.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_base_multilingual_uncased_finetuned_solidarity","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_finetuned_solidarity", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_finetuned_solidarity| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/amaurits/bert-base-multilingual-uncased-finetuned-solidarity \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_yelp_review_full_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_yelp_review_full_xx.md new file mode 100644 index 00000000000000..9277f7f06a538f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_multilingual_uncased_yelp_review_full_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_yelp_review_full BertForSequenceClassification from pbwt +author: John Snow Labs +name: bert_base_multilingual_uncased_yelp_review_full +date: 2024-09-26 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_yelp_review_full` is a Multilingual model originally trained by pbwt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_yelp_review_full_xx_5.5.0_3.0_1727364643517.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_yelp_review_full_xx_5.5.0_3.0_1727364643517.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_base_multilingual_uncased_yelp_review_full","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_yelp_review_full", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_yelp_review_full| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/pbwt/bert-base-multilingual-uncased-yelp_review_full \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_02_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_02_pipeline_en.md new file mode 100644 index 00000000000000..4e4e1972b9d772 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_02_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_portuguese_cased_02_pipeline pipeline BertForSequenceClassification from TiagoSanti +author: John Snow Labs +name: bert_base_portuguese_cased_02_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_portuguese_cased_02_pipeline` is a English model originally trained by TiagoSanti. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_02_pipeline_en_5.5.0_3.0_1727336326456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_02_pipeline_en_5.5.0_3.0_1727336326456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_portuguese_cased_02_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_portuguese_cased_02_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_portuguese_cased_02_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/TiagoSanti/bert-base-portuguese-cased-02 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_assin2_entailment_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_assin2_entailment_pipeline_pt.md new file mode 100644 index 00000000000000..a4e954abdcd60d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_assin2_entailment_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese bert_base_portuguese_cased_assin2_entailment_pipeline pipeline BertForSequenceClassification from ruanchaves +author: John Snow Labs +name: bert_base_portuguese_cased_assin2_entailment_pipeline +date: 2024-09-26 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_portuguese_cased_assin2_entailment_pipeline` is a Portuguese model originally trained by ruanchaves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_assin2_entailment_pipeline_pt_5.5.0_3.0_1727334241706.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_assin2_entailment_pipeline_pt_5.5.0_3.0_1727334241706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_portuguese_cased_assin2_entailment_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_portuguese_cased_assin2_entailment_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_portuguese_cased_assin2_entailment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|408.2 MB| + +## References + +https://huggingface.co/ruanchaves/bert-base-portuguese-cased-assin2-entailment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_faquad_nli_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_faquad_nli_pipeline_pt.md new file mode 100644 index 00000000000000..c3f6d8ba87c433 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_faquad_nli_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese bert_base_portuguese_cased_faquad_nli_pipeline pipeline BertForSequenceClassification from ruanchaves +author: John Snow Labs +name: bert_base_portuguese_cased_faquad_nli_pipeline +date: 2024-09-26 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_portuguese_cased_faquad_nli_pipeline` is a Portuguese model originally trained by ruanchaves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_faquad_nli_pipeline_pt_5.5.0_3.0_1727390287511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_faquad_nli_pipeline_pt_5.5.0_3.0_1727390287511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_portuguese_cased_faquad_nli_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_portuguese_cased_faquad_nli_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_portuguese_cased_faquad_nli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|408.2 MB| + +## References + +https://huggingface.co/ruanchaves/bert-base-portuguese-cased-faquad-nli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_faquad_nli_pt.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_faquad_nli_pt.md new file mode 100644 index 00000000000000..d4785fd62addcf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_portuguese_cased_faquad_nli_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese bert_base_portuguese_cased_faquad_nli BertForSequenceClassification from ruanchaves +author: John Snow Labs +name: bert_base_portuguese_cased_faquad_nli +date: 2024-09-26 +tags: [pt, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_portuguese_cased_faquad_nli` is a Portuguese model originally trained by ruanchaves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_faquad_nli_pt_5.5.0_3.0_1727390265564.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_portuguese_cased_faquad_nli_pt_5.5.0_3.0_1727390265564.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_base_portuguese_cased_faquad_nli","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_portuguese_cased_faquad_nli", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_portuguese_cased_faquad_nli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.2 MB| + +## References + +https://huggingface.co/ruanchaves/bert-base-portuguese-cased-faquad-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_rte_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_rte_en.md new file mode 100644 index 00000000000000..ed77cb42168592 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_rte_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_rte BertForSequenceClassification from Cheng98 +author: John Snow Labs +name: bert_base_rte +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_rte` is a English model originally trained by Cheng98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_rte_en_5.5.0_3.0_1727323263149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_rte_en_5.5.0_3.0_1727323263149.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_base_rte","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_rte", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_rte| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Cheng98/bert-base-rte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_rte_pipeline_en.md new file mode 100644 index 00000000000000..97e662eee72eb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_rte_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_rte_pipeline pipeline BertForSequenceClassification from Cheng98 +author: John Snow Labs +name: bert_base_rte_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_rte_pipeline` is a English model originally trained by Cheng98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_rte_pipeline_en_5.5.0_3.0_1727323284084.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_rte_pipeline_en_5.5.0_3.0_1727323284084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_rte_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_rte_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_rte_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Cheng98/bert-base-rte + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_en.md new file mode 100644 index 00000000000000..ee3ef5640a24db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94 BertForSequenceClassification from rBlue94 +author: John Snow Labs +name: bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_meia_analisisdesentimientos_rblue94` is a English model originally trained by rBlue94. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_en_5.5.0_3.0_1727386794634.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_meia_analisisdesentimientos_rblue94_en_5.5.0_3.0_1727386794634.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_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/rBlue94/bert-base-spanish-wwm-cased-finetuned-MeIA-AnalisisDeSentimientos \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline_en.md new file mode 100644 index 00000000000000..8a6132f404d9f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline pipeline BertForSequenceClassification from rBlue94 +author: John Snow Labs +name: bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline` is a English model originally trained by rBlue94. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline_en_5.5.0_3.0_1727386816104.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_meia_analisisdesentimientos_rblue94_pipeline_en_5.5.0_3.0_1727386816104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_finetuned_meia_analisisdesentimientos_rblue94_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/rBlue94/bert-base-spanish-wwm-cased-finetuned-MeIA-AnalisisDeSentimientos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline_en.md new file mode 100644 index 00000000000000..e82d34a10adcd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline pipeline BertForSequenceClassification from Jumartineze +author: John Snow Labs +name: bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline` is a English model originally trained by Jumartineze. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline_en_5.5.0_3.0_1727381824705.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_meia_analisisdesentimientos_jumartineze_pipeline_en_5.5.0_3.0_1727381824705.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_uncased_finetuned_meia_analisisdesentimientos_jumartineze_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/Jumartineze/bert-base-spanish-wwm-uncased-finetuned-MeIA-AnalisisDeSentimientos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_uncased_r_tag_0_3_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_uncased_r_tag_0_3_en.md new file mode 100644 index 00000000000000..712260a404b007 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_spanish_wwm_uncased_r_tag_0_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_spanish_wwm_uncased_r_tag_0_3 BertForSequenceClassification from ISA-Group +author: John Snow Labs +name: bert_base_spanish_wwm_uncased_r_tag_0_3 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_r_tag_0_3` is a English model originally trained by ISA-Group. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_r_tag_0_3_en_5.5.0_3.0_1727348803477.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_r_tag_0_3_en_5.5.0_3.0_1727348803477.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_base_spanish_wwm_uncased_r_tag_0_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_uncased_r_tag_0_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_uncased_r_tag_0_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/ISA-Group/bert-base-spanish-wwm-uncased_r-tag-0.3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_turkish_offensive_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_turkish_offensive_pipeline_tr.md new file mode 100644 index 00000000000000..b7ec4192e1d498 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_turkish_offensive_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish bert_base_turkish_offensive_pipeline pipeline BertForSequenceClassification from nanelimon +author: John Snow Labs +name: bert_base_turkish_offensive_pipeline +date: 2024-09-26 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_offensive_pipeline` is a Turkish model originally trained by nanelimon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_offensive_pipeline_tr_5.5.0_3.0_1727362689496.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_offensive_pipeline_tr_5.5.0_3.0_1727362689496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_turkish_offensive_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_turkish_offensive_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_offensive_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|691.6 MB| + +## References + +https://huggingface.co/nanelimon/bert-base-turkish-offensive + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_10_0_01_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_10_0_01_en.md new file mode 100644 index 00000000000000..71029bb89f1086 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_10_0_01_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_8_10_0_01 BertForSequenceClassification from daisyxie21 +author: John Snow Labs +name: bert_base_uncased_8_10_0_01 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_8_10_0_01` is a English model originally trained by daisyxie21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_8_10_0_01_en_5.5.0_3.0_1727378419352.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_8_10_0_01_en_5.5.0_3.0_1727378419352.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_base_uncased_8_10_0_01","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_8_10_0_01", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_8_10_0_01| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/daisyxie21/bert-base-uncased-8-10-0.01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_200_0_01_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_200_0_01_en.md new file mode 100644 index 00000000000000..268da37d6527fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_200_0_01_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_8_200_0_01 BertForSequenceClassification from daisyxie21 +author: John Snow Labs +name: bert_base_uncased_8_200_0_01 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_8_200_0_01` is a English model originally trained by daisyxie21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_8_200_0_01_en_5.5.0_3.0_1727354544822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_8_200_0_01_en_5.5.0_3.0_1727354544822.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_base_uncased_8_200_0_01","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_8_200_0_01", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_8_200_0_01| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/daisyxie21/bert-base-uncased-8-200-0.01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_200_0_01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_200_0_01_pipeline_en.md new file mode 100644 index 00000000000000..4b912f7e9d5998 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_8_200_0_01_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_8_200_0_01_pipeline pipeline BertForSequenceClassification from daisyxie21 +author: John Snow Labs +name: bert_base_uncased_8_200_0_01_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_8_200_0_01_pipeline` is a English model originally trained by daisyxie21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_8_200_0_01_pipeline_en_5.5.0_3.0_1727354566365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_8_200_0_01_pipeline_en_5.5.0_3.0_1727354566365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_8_200_0_01_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_8_200_0_01_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_8_200_0_01_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/daisyxie21/bert-base-uncased-8-200-0.01 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_delete_ag_news_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_delete_ag_news_pipeline_en.md new file mode 100644 index 00000000000000..9e406692b33a67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_delete_ag_news_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_advtrain_delete_ag_news_pipeline pipeline BertForSequenceClassification from PFEemp2024 +author: John Snow Labs +name: bert_base_uncased_advtrain_delete_ag_news_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_advtrain_delete_ag_news_pipeline` is a English model originally trained by PFEemp2024. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_advtrain_delete_ag_news_pipeline_en_5.5.0_3.0_1727379783223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_advtrain_delete_ag_news_pipeline_en_5.5.0_3.0_1727379783223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_advtrain_delete_ag_news_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_advtrain_delete_ag_news_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_advtrain_delete_ag_news_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/PFEemp2024/bert-base-uncased-AdvTrain-Delete-Ag-News + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_gradient_ag_news_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_gradient_ag_news_en.md new file mode 100644 index 00000000000000..f8d08f6dbd30fa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_gradient_ag_news_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_advtrain_gradient_ag_news BertForSequenceClassification from PFEemp2024 +author: John Snow Labs +name: bert_base_uncased_advtrain_gradient_ag_news +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_advtrain_gradient_ag_news` is a English model originally trained by PFEemp2024. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_advtrain_gradient_ag_news_en_5.5.0_3.0_1727372182963.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_advtrain_gradient_ag_news_en_5.5.0_3.0_1727372182963.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_base_uncased_advtrain_gradient_ag_news","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_advtrain_gradient_ag_news", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_advtrain_gradient_ag_news| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/PFEemp2024/bert-base-uncased-AdvTrain-Gradient-Ag-News \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_gradient_ag_news_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_gradient_ag_news_pipeline_en.md new file mode 100644 index 00000000000000..17880b145dd731 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_advtrain_gradient_ag_news_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_advtrain_gradient_ag_news_pipeline pipeline BertForSequenceClassification from PFEemp2024 +author: John Snow Labs +name: bert_base_uncased_advtrain_gradient_ag_news_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_advtrain_gradient_ag_news_pipeline` is a English model originally trained by PFEemp2024. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_advtrain_gradient_ag_news_pipeline_en_5.5.0_3.0_1727372204625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_advtrain_gradient_ag_news_pipeline_en_5.5.0_3.0_1727372204625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_advtrain_gradient_ag_news_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_advtrain_gradient_ag_news_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_advtrain_gradient_ag_news_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/PFEemp2024/bert-base-uncased-AdvTrain-Gradient-Ag-News + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ag_news_finetuned_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ag_news_finetuned_2_pipeline_en.md new file mode 100644 index 00000000000000..74db5e8681cdd5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ag_news_finetuned_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_ag_news_finetuned_2_pipeline pipeline BertForSequenceClassification from odunola +author: John Snow Labs +name: bert_base_uncased_ag_news_finetuned_2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ag_news_finetuned_2_pipeline` is a English model originally trained by odunola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ag_news_finetuned_2_pipeline_en_5.5.0_3.0_1727366196384.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_2_pipeline_en_5.5.0_3.0_1727366196384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_ag_news_finetuned_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_ag_news_finetuned_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ag_news_finetuned_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/odunola/bert-base-uncased-ag-news-finetuned-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_agnews_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_agnews_pipeline_en.md new file mode 100644 index 00000000000000..31ac32f5b1de18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_agnews_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_agnews_pipeline pipeline BertForSequenceClassification from tamhuynh27 +author: John Snow Labs +name: bert_base_uncased_agnews_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_agnews_pipeline` is a English model originally trained by tamhuynh27. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_agnews_pipeline_en_5.5.0_3.0_1727318801927.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_agnews_pipeline_en_5.5.0_3.0_1727318801927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_agnews_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_agnews_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_agnews_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tamhuynh27/bert-base-uncased-agnews + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_atis_v1_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_atis_v1_en.md new file mode 100644 index 00000000000000..fc55d1ff1bd101 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_atis_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_atis_v1 BertForSequenceClassification from benayas +author: John Snow Labs +name: bert_base_uncased_atis_v1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_atis_v1` is a English model originally trained by benayas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_atis_v1_en_5.5.0_3.0_1727380275937.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_atis_v1_en_5.5.0_3.0_1727380275937.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_base_uncased_atis_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_atis_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_atis_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.4 MB| + +## References + +https://huggingface.co/benayas/bert-base-uncased-atis-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_bahaaeldin0_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_bahaaeldin0_en.md new file mode 100644 index 00000000000000..37f02a982cdb34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_bahaaeldin0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_bahaaeldin0 BertForSequenceClassification from BahaaEldin0 +author: John Snow Labs +name: bert_base_uncased_bahaaeldin0 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_bahaaeldin0` is a English model originally trained by BahaaEldin0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_bahaaeldin0_en_5.5.0_3.0_1727382868902.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_bahaaeldin0_en_5.5.0_3.0_1727382868902.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_base_uncased_bahaaeldin0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_bahaaeldin0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_bahaaeldin0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/BahaaEldin0/bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_bahaaeldin0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_bahaaeldin0_pipeline_en.md new file mode 100644 index 00000000000000..02c46cef1eac4a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_bahaaeldin0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_bahaaeldin0_pipeline pipeline BertForSequenceClassification from BahaaEldin0 +author: John Snow Labs +name: bert_base_uncased_bahaaeldin0_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_bahaaeldin0_pipeline` is a English model originally trained by BahaaEldin0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_bahaaeldin0_pipeline_en_5.5.0_3.0_1727382892077.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_bahaaeldin0_pipeline_en_5.5.0_3.0_1727382892077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_bahaaeldin0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_bahaaeldin0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_bahaaeldin0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/BahaaEldin0/bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cagr_mypersonality_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cagr_mypersonality_en.md new file mode 100644 index 00000000000000..ab4cf40f0a30c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cagr_mypersonality_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_cagr_mypersonality BertForSequenceClassification from holistic-ai +author: John Snow Labs +name: bert_base_uncased_cagr_mypersonality +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_cagr_mypersonality` is a English model originally trained by holistic-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cagr_mypersonality_en_5.5.0_3.0_1727310687090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cagr_mypersonality_en_5.5.0_3.0_1727310687090.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_base_uncased_cagr_mypersonality","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cagr_mypersonality", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cagr_mypersonality| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/holistic-ai/bert-base-uncased_cAGR_mypersonality \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_classification_flat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_classification_flat_pipeline_en.md new file mode 100644 index 00000000000000..7af17dea1cda23 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_classification_flat_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_classification_flat_pipeline pipeline BertForSequenceClassification from irfanamal +author: John Snow Labs +name: bert_base_uncased_classification_flat_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_classification_flat_pipeline` is a English model originally trained by irfanamal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_classification_flat_pipeline_en_5.5.0_3.0_1727353295081.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_classification_flat_pipeline_en_5.5.0_3.0_1727353295081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_classification_flat_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_classification_flat_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_classification_flat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.0 MB| + +## References + +https://huggingface.co/irfanamal/bert-base-uncased-classification-flat + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_clickbait_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_clickbait_en.md new file mode 100644 index 00000000000000..39c3bb17f1e52e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_clickbait_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_clickbait BertForSequenceClassification from Stremie +author: John Snow Labs +name: bert_base_uncased_clickbait +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_clickbait` is a English model originally trained by Stremie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_clickbait_en_5.5.0_3.0_1727379900351.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_clickbait_en_5.5.0_3.0_1727379900351.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_base_uncased_clickbait","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_clickbait", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_clickbait| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Stremie/bert-base-uncased-clickbait \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_clickbait_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_clickbait_pipeline_en.md new file mode 100644 index 00000000000000..018e0e03d4fbde --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_clickbait_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_clickbait_pipeline pipeline BertForSequenceClassification from Stremie +author: John Snow Labs +name: bert_base_uncased_clickbait_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_clickbait_pipeline` is a English model originally trained by Stremie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_clickbait_pipeline_en_5.5.0_3.0_1727379922455.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_clickbait_pipeline_en_5.5.0_3.0_1727379922455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_clickbait_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_clickbait_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_clickbait_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Stremie/bert-base-uncased-clickbait + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_epochs_10_lr_5e_05_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_epochs_10_lr_5e_05_en.md new file mode 100644 index 00000000000000..33bb2b794eac58 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_epochs_10_lr_5e_05_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_cola_epochs_10_lr_5e_05 BertForSequenceClassification from prateeky2806 +author: John Snow Labs +name: bert_base_uncased_cola_epochs_10_lr_5e_05 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_epochs_10_lr_5e_05` is a English model originally trained by prateeky2806. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_epochs_10_lr_5e_05_en_5.5.0_3.0_1727335009851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_epochs_10_lr_5e_05_en_5.5.0_3.0_1727335009851.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_base_uncased_cola_epochs_10_lr_5e_05","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cola_epochs_10_lr_5e_05", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cola_epochs_10_lr_5e_05| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/prateeky2806/bert-base-uncased-cola-epochs-10-lr-5e-05 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_howey_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_howey_en.md new file mode 100644 index 00000000000000..cb9a8dcab332a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_howey_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_cola_howey BertForSequenceClassification from howey +author: John Snow Labs +name: bert_base_uncased_cola_howey +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_howey` is a English model originally trained by howey. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_howey_en_5.5.0_3.0_1727374472544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_howey_en_5.5.0_3.0_1727374472544.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_base_uncased_cola_howey","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cola_howey", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cola_howey| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/howey/bert-base-uncased-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_howey_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_howey_pipeline_en.md new file mode 100644 index 00000000000000..3e2daed5bfe8b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_cola_howey_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_cola_howey_pipeline pipeline BertForSequenceClassification from howey +author: John Snow Labs +name: bert_base_uncased_cola_howey_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_cola_howey_pipeline` is a English model originally trained by howey. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_howey_pipeline_en_5.5.0_3.0_1727374494185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_howey_pipeline_en_5.5.0_3.0_1727374494185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_cola_howey_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_cola_howey_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cola_howey_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/howey/bert-base-uncased-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_customsentiments_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_customsentiments_en.md new file mode 100644 index 00000000000000..75643ed43f0fd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_customsentiments_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_customsentiments BertForSequenceClassification from Shreyagg2202 +author: John Snow Labs +name: bert_base_uncased_customsentiments +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_customsentiments` is a English model originally trained by Shreyagg2202. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_customsentiments_en_5.5.0_3.0_1727374777494.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_customsentiments_en_5.5.0_3.0_1727374777494.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_base_uncased_customsentiments","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_customsentiments", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_customsentiments| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Shreyagg2202/bert-base-uncased-CustomSentiments \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_customsentiments_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_customsentiments_pipeline_en.md new file mode 100644 index 00000000000000..98eaec82129619 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_customsentiments_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_customsentiments_pipeline pipeline BertForSequenceClassification from Shreyagg2202 +author: John Snow Labs +name: bert_base_uncased_customsentiments_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_customsentiments_pipeline` is a English model originally trained by Shreyagg2202. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_customsentiments_pipeline_en_5.5.0_3.0_1727374798898.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_customsentiments_pipeline_en_5.5.0_3.0_1727374798898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_customsentiments_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_customsentiments_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_customsentiments_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Shreyagg2202/bert-base-uncased-CustomSentiments + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline_en.md new file mode 100644 index 00000000000000..757f0d60001d28 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline pipeline BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline_en_5.5.0_3.0_1727382670819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline_en_5.5.0_3.0_1727382670819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_deletion_multiclass_label_removed_complete_final_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/research-dump/bert-base-uncased_deletion_multiclass_label_removed_complete_final + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_do_finetuned_cola_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_do_finetuned_cola_en.md new file mode 100644 index 00000000000000..8216d164741cb1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_do_finetuned_cola_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_do_finetuned_cola BertForSequenceClassification from berkozcelik +author: John Snow Labs +name: bert_base_uncased_do_finetuned_cola +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_do_finetuned_cola` is a English model originally trained by berkozcelik. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_do_finetuned_cola_en_5.5.0_3.0_1727381035056.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_do_finetuned_cola_en_5.5.0_3.0_1727381035056.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_base_uncased_do_finetuned_cola","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_do_finetuned_cola", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_do_finetuned_cola| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/berkozcelik/bert-base-uncased-do-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline_en.md new file mode 100644 index 00000000000000..c8d7302a6b0047 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline pipeline BertForSequenceClassification from wilsontam +author: John Snow Labs +name: bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline` is a English model originally trained by wilsontam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline_en_5.5.0_3.0_1727325963823.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline_en_5.5.0_3.0_1727325963823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_dstc10_knowledge_cluster_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.5 MB| + +## References + +https://huggingface.co/wilsontam/bert-base-uncased-dstc10-knowledge-cluster-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_fituned_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_fituned_en.md new file mode 100644 index 00000000000000..f723aeb3a2dc86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_fituned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_emotion_fituned BertForSequenceClassification from sonia12138 +author: John Snow Labs +name: bert_base_uncased_emotion_fituned +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_fituned` is a English model originally trained by sonia12138. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_fituned_en_5.5.0_3.0_1727374932182.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_fituned_en_5.5.0_3.0_1727374932182.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_base_uncased_emotion_fituned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_emotion_fituned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_fituned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sonia12138/bert-base-uncased-emotion-fituned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_mooncrescent_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_mooncrescent_pipeline_en.md new file mode 100644 index 00000000000000..16925f6ee11c16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_mooncrescent_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_emotion_mooncrescent_pipeline pipeline BertForSequenceClassification from MoonCrescent +author: John Snow Labs +name: bert_base_uncased_emotion_mooncrescent_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_emotion_mooncrescent_pipeline` is a English model originally trained by MoonCrescent. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_mooncrescent_pipeline_en_5.5.0_3.0_1727338445481.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_mooncrescent_pipeline_en_5.5.0_3.0_1727338445481.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_emotion_mooncrescent_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_emotion_mooncrescent_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_mooncrescent_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MoonCrescent/bert-base-uncased-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_palmer0_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_palmer0_en.md new file mode 100644 index 00000000000000..7984b435ce2ebd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_palmer0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_emotion_palmer0 BertForSequenceClassification from palmer0 +author: John Snow Labs +name: bert_base_uncased_emotion_palmer0 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_palmer0` is a English model originally trained by palmer0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_palmer0_en_5.5.0_3.0_1727383624538.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_palmer0_en_5.5.0_3.0_1727383624538.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_base_uncased_emotion_palmer0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_emotion_palmer0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_palmer0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/palmer0/bert-base-uncased-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_palmer0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_palmer0_pipeline_en.md new file mode 100644 index 00000000000000..bf893bb5efa740 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotion_palmer0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_emotion_palmer0_pipeline pipeline BertForSequenceClassification from palmer0 +author: John Snow Labs +name: bert_base_uncased_emotion_palmer0_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_emotion_palmer0_pipeline` is a English model originally trained by palmer0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_palmer0_pipeline_en_5.5.0_3.0_1727383646704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_palmer0_pipeline_en_5.5.0_3.0_1727383646704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_emotion_palmer0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_emotion_palmer0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_palmer0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/palmer0/bert-base-uncased-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotions_augmented_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotions_augmented_pipeline_en.md new file mode 100644 index 00000000000000..3482c95c779a25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_emotions_augmented_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_emotions_augmented_pipeline pipeline BertForSequenceClassification from gabrielsgaspar +author: John Snow Labs +name: bert_base_uncased_emotions_augmented_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_emotions_augmented_pipeline` is a English model originally trained by gabrielsgaspar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotions_augmented_pipeline_en_5.5.0_3.0_1727380966455.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotions_augmented_pipeline_en_5.5.0_3.0_1727380966455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_emotions_augmented_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_emotions_augmented_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotions_augmented_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gabrielsgaspar/bert-base-uncased-emotions-augmented + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained_en.md new file mode 100644 index 00000000000000..9bc66b03572f11 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained BertForSequenceClassification from adutlersaar +author: John Snow Labs +name: bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained` is a English model originally trained by adutlersaar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained_en_5.5.0_3.0_1727383947543.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained_en_5.5.0_3.0_1727383947543.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_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_fine_tuned_parler_data_norwegian_bart_with_t5_norwegian_bpe_adv_trained| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/adutlersaar/bert-base-uncased-fine-tuned-parler_data-no_bart-with_t5-no_bpe-adv-trained \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetune_accidents_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetune_accidents_en.md new file mode 100644 index 00000000000000..eea1bf98765519 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetune_accidents_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetune_accidents BertForSequenceClassification from Alec42 +author: John Snow Labs +name: bert_base_uncased_finetune_accidents +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_finetune_accidents` is a English model originally trained by Alec42. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_accidents_en_5.5.0_3.0_1727378205230.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_accidents_en_5.5.0_3.0_1727378205230.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_base_uncased_finetune_accidents","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetune_accidents", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetune_accidents| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Alec42/bert-base-uncased-finetune-accidents \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetune_accidents_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetune_accidents_pipeline_en.md new file mode 100644 index 00000000000000..6eef646d2526ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetune_accidents_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetune_accidents_pipeline pipeline BertForSequenceClassification from Alec42 +author: John Snow Labs +name: bert_base_uncased_finetune_accidents_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetune_accidents_pipeline` is a English model originally trained by Alec42. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_accidents_pipeline_en_5.5.0_3.0_1727378227825.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetune_accidents_pipeline_en_5.5.0_3.0_1727378227825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetune_accidents_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetune_accidents_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetune_accidents_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Alec42/bert-base-uncased-finetune-accidents + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_10epoch_num200_450_405cls_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_10epoch_num200_450_405cls_en.md new file mode 100644 index 00000000000000..84cb7f899f27bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_10epoch_num200_450_405cls_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_10epoch_num200_450_405cls BertForSequenceClassification from liangyuant +author: John Snow Labs +name: bert_base_uncased_finetuned_10epoch_num200_450_405cls +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_10epoch_num200_450_405cls` is a English model originally trained by liangyuant. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_10epoch_num200_450_405cls_en_5.5.0_3.0_1727350782688.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_10epoch_num200_450_405cls_en_5.5.0_3.0_1727350782688.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_base_uncased_finetuned_10epoch_num200_450_405cls","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_10epoch_num200_450_405cls", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_10epoch_num200_450_405cls| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.6 MB| + +## References + +https://huggingface.co/liangyuant/bert-base-uncased-finetuned-10epoch-num200-450-405cls \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_argument_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_argument_detection_pipeline_en.md new file mode 100644 index 00000000000000..27347dbfa02617 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_argument_detection_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_argument_detection_pipeline pipeline BertForSequenceClassification from vzty +author: John Snow Labs +name: bert_base_uncased_finetuned_argument_detection_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_argument_detection_pipeline` is a English model originally trained by vzty. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_argument_detection_pipeline_en_5.5.0_3.0_1727350117462.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_argument_detection_pipeline_en_5.5.0_3.0_1727350117462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_argument_detection_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_argument_detection_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_argument_detection_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/vzty/bert-base-uncased-finetuned-argument-detection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_climate_stance_detection_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_climate_stance_detection_en.md new file mode 100644 index 00000000000000..62a528c74d7da2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_climate_stance_detection_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_climate_stance_detection BertForSequenceClassification from rldekkers +author: John Snow Labs +name: bert_base_uncased_finetuned_climate_stance_detection +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_stance_detection` is a English model originally trained by rldekkers. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_climate_stance_detection_en_5.5.0_3.0_1727386933820.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_climate_stance_detection_en_5.5.0_3.0_1727386933820.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_base_uncased_finetuned_climate_stance_detection","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_climate_stance_detection", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_climate_stance_detection| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rldekkers/bert-base-uncased-finetuned-climate-stance-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_2_en.md new file mode 100644 index 00000000000000..77f03cf936fcac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_2 BertForSequenceClassification from kdo6301 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_2` is a English model originally trained by kdo6301. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_2_en_5.5.0_3.0_1727374967884.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_2_en_5.5.0_3.0_1727374967884.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_base_uncased_finetuned_cola_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kdo6301/bert-base-uncased-finetuned-cola-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_2_pipeline_en.md new file mode 100644 index 00000000000000..5211ffdc0b206c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_2_pipeline pipeline BertForSequenceClassification from kdo6301 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_2_pipeline` is a English model originally trained by kdo6301. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_2_pipeline_en_5.5.0_3.0_1727374992709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_2_pipeline_en_5.5.0_3.0_1727374992709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kdo6301/bert-base-uncased-finetuned-cola-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_alemdarberk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_alemdarberk_pipeline_en.md new file mode 100644 index 00000000000000..4c0c75034ba7ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_alemdarberk_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_alemdarberk_pipeline pipeline BertForSequenceClassification from alemdarberk +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_alemdarberk_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_alemdarberk_pipeline` is a English model originally trained by alemdarberk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_alemdarberk_pipeline_en_5.5.0_3.0_1727320978655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_alemdarberk_pipeline_en_5.5.0_3.0_1727320978655.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_alemdarberk_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_alemdarberk_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_alemdarberk_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/alemdarberk/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_anilbayramg_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_anilbayramg_en.md new file mode 100644 index 00000000000000..94651bba918db3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_anilbayramg_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_anilbayramg BertForSequenceClassification from anilbayramg +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_anilbayramg +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_anilbayramg` is a English model originally trained by anilbayramg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_anilbayramg_en_5.5.0_3.0_1727384710718.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_anilbayramg_en_5.5.0_3.0_1727384710718.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_base_uncased_finetuned_cola_anilbayramg","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_anilbayramg", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_anilbayramg| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/anilbayramg/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_anilbayramg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_anilbayramg_pipeline_en.md new file mode 100644 index 00000000000000..df9b8f154b8be0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_anilbayramg_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_anilbayramg_pipeline pipeline BertForSequenceClassification from anilbayramg +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_anilbayramg_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_anilbayramg_pipeline` is a English model originally trained by anilbayramg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_anilbayramg_pipeline_en_5.5.0_3.0_1727384732952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_anilbayramg_pipeline_en_5.5.0_3.0_1727384732952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_anilbayramg_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_anilbayramg_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_anilbayramg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/anilbayramg/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_16_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_16_en.md new file mode 100644 index 00000000000000..b903933937a5be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_16_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_batch_16 BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_batch_16 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_batch_16` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_batch_16_en_5.5.0_3.0_1727385407371.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_batch_16_en_5.5.0_3.0_1727385407371.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_base_uncased_finetuned_cola_batch_16","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_batch_16", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_batch_16| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-batch-16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_16_pipeline_en.md new file mode 100644 index 00000000000000..af176fd95ce975 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_16_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_batch_16_pipeline pipeline BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_batch_16_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_batch_16_pipeline` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_batch_16_pipeline_en_5.5.0_3.0_1727385432184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_batch_16_pipeline_en_5.5.0_3.0_1727385432184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_batch_16_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_batch_16_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_batch_16_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-batch-16 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_2_en.md new file mode 100644 index 00000000000000..88b2c90de00d46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_batch_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_batch_2 BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_batch_2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_batch_2` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_batch_2_en_5.5.0_3.0_1727387670714.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_batch_2_en_5.5.0_3.0_1727387670714.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_base_uncased_finetuned_cola_batch_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_batch_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_batch_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-batch-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_ga21902298_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_ga21902298_en.md new file mode 100644 index 00000000000000..8864e0aa1b1de5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_ga21902298_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_ga21902298 BertForSequenceClassification from ga21902298 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_ga21902298 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ga21902298` is a English model originally trained by ga21902298. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ga21902298_en_5.5.0_3.0_1727381708272.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ga21902298_en_5.5.0_3.0_1727381708272.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_base_uncased_finetuned_cola_ga21902298","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_ga21902298", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_ga21902298| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ga21902298/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_gulce_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_gulce_pipeline_en.md new file mode 100644 index 00000000000000..2829c4421439b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_gulce_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_gulce_pipeline pipeline BertForSequenceClassification from Gulce +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_gulce_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_gulce_pipeline` is a English model originally trained by Gulce. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_gulce_pipeline_en_5.5.0_3.0_1727388632546.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_gulce_pipeline_en_5.5.0_3.0_1727388632546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_gulce_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_gulce_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_gulce_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.1 MB| + +## References + +https://huggingface.co/Gulce/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_hmert00_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_hmert00_pipeline_en.md new file mode 100644 index 00000000000000..13a9ad5f2a86b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_hmert00_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_hmert00_pipeline pipeline BertForSequenceClassification from hmert00 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_hmert00_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_hmert00_pipeline` is a English model originally trained by hmert00. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_hmert00_pipeline_en_5.5.0_3.0_1727384113962.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_hmert00_pipeline_en_5.5.0_3.0_1727384113962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_hmert00_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_hmert00_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_hmert00_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/hmert00/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_kdo6301_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_kdo6301_en.md new file mode 100644 index 00000000000000..ce9b8e941c4150 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_kdo6301_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_kdo6301 BertForSequenceClassification from kdo6301 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_kdo6301 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_kdo6301` is a English model originally trained by kdo6301. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_kdo6301_en_5.5.0_3.0_1727378514464.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_kdo6301_en_5.5.0_3.0_1727378514464.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_base_uncased_finetuned_cola_kdo6301","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_kdo6301", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_kdo6301| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kdo6301/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_kdo6301_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_kdo6301_pipeline_en.md new file mode 100644 index 00000000000000..19169575ecdc2a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_kdo6301_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_kdo6301_pipeline pipeline BertForSequenceClassification from kdo6301 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_kdo6301_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_kdo6301_pipeline` is a English model originally trained by kdo6301. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_kdo6301_pipeline_en_5.5.0_3.0_1727378535945.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_kdo6301_pipeline_en_5.5.0_3.0_1727378535945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_kdo6301_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_kdo6301_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_kdo6301_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kdo6301/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_learning_rate_4e_05_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_learning_rate_4e_05_en.md new file mode 100644 index 00000000000000..3f043b0d7edbca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_learning_rate_4e_05_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_learning_rate_4e_05 BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_learning_rate_4e_05 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_learning_rate_4e_05` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_learning_rate_4e_05_en_5.5.0_3.0_1727385554385.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_learning_rate_4e_05_en_5.5.0_3.0_1727385554385.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_base_uncased_finetuned_cola_learning_rate_4e_05","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_learning_rate_4e_05", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_learning_rate_4e_05| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-learning_rate-4e-05 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline_en.md new file mode 100644 index 00000000000000..92557b15341881 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline pipeline BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline_en_5.5.0_3.0_1727385575413.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline_en_5.5.0_3.0_1727385575413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_learning_rate_4e_05_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-learning_rate-4e-05 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_p0uy4_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_p0uy4_en.md new file mode 100644 index 00000000000000..92f0c17c81e780 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_p0uy4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_p0uy4 BertForSequenceClassification from p0uy4 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_p0uy4 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_p0uy4` is a English model originally trained by p0uy4. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_p0uy4_en_5.5.0_3.0_1727386580904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_p0uy4_en_5.5.0_3.0_1727386580904.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_base_uncased_finetuned_cola_p0uy4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_p0uy4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_p0uy4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/p0uy4/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_p0uy4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_p0uy4_pipeline_en.md new file mode 100644 index 00000000000000..38f95a93716094 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_p0uy4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_p0uy4_pipeline pipeline BertForSequenceClassification from p0uy4 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_p0uy4_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_p0uy4_pipeline` is a English model originally trained by p0uy4. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_p0uy4_pipeline_en_5.5.0_3.0_1727386602547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_p0uy4_pipeline_en_5.5.0_3.0_1727386602547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_p0uy4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_p0uy4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_p0uy4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/p0uy4/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_final_last_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_final_last_en.md new file mode 100644 index 00000000000000..bb8ecc1e1bac63 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_final_last_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_sepehr_final_last BertForSequenceClassification from sepehrbakhshi +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_sepehr_final_last +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sepehr_final_last` is a English model originally trained by sepehrbakhshi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_final_last_en_5.5.0_3.0_1727385740357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_final_last_en_5.5.0_3.0_1727385740357.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_base_uncased_finetuned_cola_sepehr_final_last","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_sepehr_final_last", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_sepehr_final_last| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sepehrbakhshi/bert-base-uncased-finetuned-cola_sepehr_final_last \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline_en.md new file mode 100644 index 00000000000000..ab0583bbbd8e40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline pipeline BertForSequenceClassification from sepehrbakhshi +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline` is a English model originally trained by sepehrbakhshi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline_en_5.5.0_3.0_1727385762342.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline_en_5.5.0_3.0_1727385762342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_sepehr_final_last_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sepehrbakhshi/bert-base-uncased-finetuned-cola_sepehr_final_last + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_sepehr_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_sepehr_en.md new file mode 100644 index 00000000000000..46af38d4f1b54e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_sepehr_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_sepehr_sepehr BertForSequenceClassification from sepehrbakhshi +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_sepehr_sepehr +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sepehr_sepehr` is a English model originally trained by sepehrbakhshi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_sepehr_en_5.5.0_3.0_1727385065944.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_sepehr_en_5.5.0_3.0_1727385065944.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_base_uncased_finetuned_cola_sepehr_sepehr","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_sepehr_sepehr", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_sepehr_sepehr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sepehrbakhshi/bert-base-uncased-finetuned-cola_sepehr_sepehr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline_en.md new file mode 100644 index 00000000000000..1082524dee0d88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline pipeline BertForSequenceClassification from sepehrbakhshi +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline` is a English model originally trained by sepehrbakhshi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline_en_5.5.0_3.0_1727352601196.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline_en_5.5.0_3.0_1727352601196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_nepal_bhasa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sepehrbakhshi/bert-base-uncased-finetuned-cola_sepehr_sepehr_sepehr_saturday_new + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_dmitva_ai_and_human_generated_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_dmitva_ai_and_human_generated_en.md new file mode 100644 index 00000000000000..f9f28a30afb0fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_dmitva_ai_and_human_generated_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_dmitva_ai_and_human_generated BertForSequenceClassification from SkwarczynskiP +author: John Snow Labs +name: bert_base_uncased_finetuned_dmitva_ai_and_human_generated +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_dmitva_ai_and_human_generated` is a English model originally trained by SkwarczynskiP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_dmitva_ai_and_human_generated_en_5.5.0_3.0_1727324968027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_dmitva_ai_and_human_generated_en_5.5.0_3.0_1727324968027.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_base_uncased_finetuned_dmitva_ai_and_human_generated","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_dmitva_ai_and_human_generated", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_dmitva_ai_and_human_generated| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/SkwarczynskiP/bert-base-uncased-finetuned-dmitva-AI-and-human-generated \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_emotion_alsaadiask_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_emotion_alsaadiask_en.md new file mode 100644 index 00000000000000..20b15cb781137e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_emotion_alsaadiask_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_emotion_alsaadiask BertForSequenceClassification from Alsaadiask +author: John Snow Labs +name: bert_base_uncased_finetuned_emotion_alsaadiask +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_emotion_alsaadiask` is a English model originally trained by Alsaadiask. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_emotion_alsaadiask_en_5.5.0_3.0_1727385398722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_emotion_alsaadiask_en_5.5.0_3.0_1727385398722.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_base_uncased_finetuned_emotion_alsaadiask","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_emotion_alsaadiask", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_emotion_alsaadiask| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Alsaadiask/bert-base-uncased-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_emotion_forna_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_emotion_forna_en.md new file mode 100644 index 00000000000000..078562c7f77663 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_emotion_forna_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_emotion_forna BertForSequenceClassification from Forna +author: John Snow Labs +name: bert_base_uncased_finetuned_emotion_forna +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_emotion_forna` is a English model originally trained by Forna. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_emotion_forna_en_5.5.0_3.0_1727352178059.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_emotion_forna_en_5.5.0_3.0_1727352178059.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_base_uncased_finetuned_emotion_forna","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_emotion_forna", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_emotion_forna| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Forna/bert-base-uncased-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_filtered_0601_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_filtered_0601_en.md new file mode 100644 index 00000000000000..941b47b09b3a0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_filtered_0601_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_filtered_0601 BertForSequenceClassification from YeRyeongLee +author: John Snow Labs +name: bert_base_uncased_finetuned_filtered_0601 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_filtered_0601` is a English model originally trained by YeRyeongLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_filtered_0601_en_5.5.0_3.0_1727342609919.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_filtered_0601_en_5.5.0_3.0_1727342609919.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_base_uncased_finetuned_filtered_0601","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_filtered_0601", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_filtered_0601| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/YeRyeongLee/bert-base-uncased-finetuned-filtered-0601 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_filtered_0609_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_filtered_0609_en.md new file mode 100644 index 00000000000000..9bf5b21534d9c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_filtered_0609_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_filtered_0609 BertForSequenceClassification from YeRyeongLee +author: John Snow Labs +name: bert_base_uncased_finetuned_filtered_0609 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_filtered_0609` is a English model originally trained by YeRyeongLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_filtered_0609_en_5.5.0_3.0_1727346240940.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_filtered_0609_en_5.5.0_3.0_1727346240940.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_base_uncased_finetuned_filtered_0609","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_filtered_0609", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_filtered_0609| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/YeRyeongLee/bert-base-uncased-finetuned-filtered-0609 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_imdb_hazardous_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_imdb_hazardous_en.md new file mode 100644 index 00000000000000..b9ba63b85b2b9c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_imdb_hazardous_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_imdb_hazardous BertForSequenceClassification from hazardous +author: John Snow Labs +name: bert_base_uncased_finetuned_imdb_hazardous +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_imdb_hazardous` is a English model originally trained by hazardous. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_imdb_hazardous_en_5.5.0_3.0_1727365928547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_imdb_hazardous_en_5.5.0_3.0_1727365928547.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_base_uncased_finetuned_imdb_hazardous","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_imdb_hazardous", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_imdb_hazardous| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/hazardous/bert_base_uncased_finetuned_imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_learningrate_2_cola_3e_05_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_learningrate_2_cola_3e_05_en.md new file mode 100644 index 00000000000000..15bf89ef168a7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_learningrate_2_cola_3e_05_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_learningrate_2_cola_3e_05 BertForSequenceClassification from yagmurery +author: John Snow Labs +name: bert_base_uncased_finetuned_learningrate_2_cola_3e_05 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_learningrate_2_cola_3e_05` is a English model originally trained by yagmurery. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_learningrate_2_cola_3e_05_en_5.5.0_3.0_1727353091584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_learningrate_2_cola_3e_05_en_5.5.0_3.0_1727353091584.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_base_uncased_finetuned_learningrate_2_cola_3e_05","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_learningrate_2_cola_3e_05", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_learningrate_2_cola_3e_05| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yagmurery/bert-base-uncased-finetuned-learningRate-2-cola-3e-05 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline_en.md new file mode 100644 index 00000000000000..cac4de9df5e08f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline pipeline BertForSequenceClassification from Gregorig +author: John Snow Labs +name: bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline` is a English model originally trained by Gregorig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline_en_5.5.0_3.0_1727346878410.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline_en_5.5.0_3.0_1727346878410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_m_avoid_harm_seler_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Gregorig/bert-base-uncased-finetuned-m_avoid_harm_seler + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_512_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_512_10_pipeline_en.md new file mode 100644 index 00000000000000..11c208bfc17c9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_512_10_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_512_10_pipeline pipeline BertForSequenceClassification from yy642 +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_512_10_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mnli_512_10_pipeline` is a English model originally trained by yy642. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_512_10_pipeline_en_5.5.0_3.0_1727384107791.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_512_10_pipeline_en_5.5.0_3.0_1727384107791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mnli_512_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mnli_512_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_512_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-512-10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_en.md new file mode 100644 index 00000000000000..9ce7df43f8dc5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_max_length_256_epoch_10 BertForSequenceClassification from yy642 +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_max_length_256_epoch_10 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mnli_max_length_256_epoch_10` is a English model originally trained by yy642. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_en_5.5.0_3.0_1727319602792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_en_5.5.0_3.0_1727319602792.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_base_uncased_finetuned_mnli_max_length_256_epoch_10","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mnli_max_length_256_epoch_10", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_max_length_256_epoch_10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-max-length-256-epoch-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline_en.md new file mode 100644 index 00000000000000..875ec19f7358b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline pipeline BertForSequenceClassification from yy642 +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline` is a English model originally trained by yy642. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline_en_5.5.0_3.0_1727319624752.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline_en_5.5.0_3.0_1727319624752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_max_length_256_epoch_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-max-length-256-epoch-10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_rte_wnli_5_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_rte_wnli_5_en.md new file mode 100644 index 00000000000000..04c3ff53969f07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_rte_wnli_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_rte_wnli_5 BertForSequenceClassification from yy642 +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_rte_wnli_5 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mnli_rte_wnli_5` is a English model originally trained by yy642. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_rte_wnli_5_en_5.5.0_3.0_1727346337700.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_rte_wnli_5_en_5.5.0_3.0_1727346337700.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_base_uncased_finetuned_mnli_rte_wnli_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mnli_rte_wnli_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_rte_wnli_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-rte-wnli-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_senfu_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_senfu_en.md new file mode 100644 index 00000000000000..2c8660ed9e854e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_senfu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_senfu BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_senfu +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mnli_senfu` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_senfu_en_5.5.0_3.0_1727384303201.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_senfu_en_5.5.0_3.0_1727384303201.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_base_uncased_finetuned_mnli_senfu","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mnli_senfu", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_senfu| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-finetuned-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_senfu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_senfu_pipeline_en.md new file mode 100644 index 00000000000000..cf64a200b2dd3d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mnli_senfu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_senfu_pipeline pipeline BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_senfu_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mnli_senfu_pipeline` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_senfu_pipeline_en_5.5.0_3.0_1727384325041.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_senfu_pipeline_en_5.5.0_3.0_1727384325041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mnli_senfu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mnli_senfu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_senfu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-finetuned-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mrpc_amrezkazemi_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mrpc_amrezkazemi_en.md new file mode 100644 index 00000000000000..2da0b96de151b9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mrpc_amrezkazemi_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mrpc_amrezkazemi BertForSequenceClassification from amrezkazemi +author: John Snow Labs +name: bert_base_uncased_finetuned_mrpc_amrezkazemi +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_amrezkazemi` is a English model originally trained by amrezkazemi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_amrezkazemi_en_5.5.0_3.0_1727375143495.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_amrezkazemi_en_5.5.0_3.0_1727375143495.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_base_uncased_finetuned_mrpc_amrezkazemi","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_amrezkazemi", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mrpc_amrezkazemi| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/amrezkazemi/bert-base-uncased-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline_en.md new file mode 100644 index 00000000000000..43627615814b50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline pipeline BertForSequenceClassification from amrezkazemi +author: John Snow Labs +name: bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline` is a English model originally trained by amrezkazemi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline_en_5.5.0_3.0_1727375165679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline_en_5.5.0_3.0_1727375165679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mrpc_amrezkazemi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/amrezkazemi/bert-base-uncased-finetuned-mrpc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_news_kushalramaiya_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_news_kushalramaiya_en.md new file mode 100644 index 00000000000000..9accfdeeb2a313 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_news_kushalramaiya_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_news_kushalramaiya BertForSequenceClassification from KushalRamaiya +author: John Snow Labs +name: bert_base_uncased_finetuned_news_kushalramaiya +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_news_kushalramaiya` is a English model originally trained by KushalRamaiya. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_kushalramaiya_en_5.5.0_3.0_1727322418085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_news_kushalramaiya_en_5.5.0_3.0_1727322418085.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_base_uncased_finetuned_news_kushalramaiya","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_news_kushalramaiya", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_news_kushalramaiya| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/KushalRamaiya/bert-base-uncased-finetuned-news \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_qnli_senfu_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_qnli_senfu_en.md new file mode 100644 index 00000000000000..7a87bbb64d5d32 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_qnli_senfu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_qnli_senfu BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_finetuned_qnli_senfu +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_senfu` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_qnli_senfu_en_5.5.0_3.0_1727355184389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_qnli_senfu_en_5.5.0_3.0_1727355184389.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_base_uncased_finetuned_qnli_senfu","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_qnli_senfu", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_qnli_senfu| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-finetuned-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_sql_classification_with_question_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_sql_classification_with_question_pipeline_en.md new file mode 100644 index 00000000000000..b663ee2b7788e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_sql_classification_with_question_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sql_classification_with_question_pipeline pipeline BertForSequenceClassification from PatWang +author: John Snow Labs +name: bert_base_uncased_finetuned_sql_classification_with_question_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_sql_classification_with_question_pipeline` is a English model originally trained by PatWang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sql_classification_with_question_pipeline_en_5.5.0_3.0_1727339547474.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sql_classification_with_question_pipeline_en_5.5.0_3.0_1727339547474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_sql_classification_with_question_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_sql_classification_with_question_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sql_classification_with_question_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/PatWang/bert-base-uncased-finetuned-sql-classification-with_question + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_sst2_bahija_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_sst2_bahija_en.md new file mode 100644 index 00000000000000..8ba1c7846ebb78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_sst2_bahija_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sst2_bahija BertForSequenceClassification from BAHIJA +author: John Snow Labs +name: bert_base_uncased_finetuned_sst2_bahija +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sst2_bahija` is a English model originally trained by BAHIJA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_bahija_en_5.5.0_3.0_1727382862514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_bahija_en_5.5.0_3.0_1727382862514.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_base_uncased_finetuned_sst2_bahija","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sst2_bahija", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sst2_bahija| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/BAHIJA/bert-base-uncased-finetuned-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_stsb_senfu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_stsb_senfu_pipeline_en.md new file mode 100644 index 00000000000000..fae2923706783f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_stsb_senfu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_stsb_senfu_pipeline pipeline BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_finetuned_stsb_senfu_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_stsb_senfu_pipeline` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_stsb_senfu_pipeline_en_5.5.0_3.0_1727393751124.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_stsb_senfu_pipeline_en_5.5.0_3.0_1727393751124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_stsb_senfu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_stsb_senfu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_stsb_senfu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-finetuned-stsb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_vr_comfort_2125_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_vr_comfort_2125_en.md new file mode 100644 index 00000000000000..cdeab890a49403 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_vr_comfort_2125_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_vr_comfort_2125 BertForSequenceClassification from jasonsheih +author: John Snow Labs +name: bert_base_uncased_finetuned_vr_comfort_2125 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_vr_comfort_2125` is a English model originally trained by jasonsheih. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_vr_comfort_2125_en_5.5.0_3.0_1727381975688.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_vr_comfort_2125_en_5.5.0_3.0_1727381975688.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_base_uncased_finetuned_vr_comfort_2125","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_vr_comfort_2125", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_vr_comfort_2125| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jasonsheih/bert-base-uncased-finetuned-vr-comfort-2125 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_vr_comfort_2125_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_vr_comfort_2125_pipeline_en.md new file mode 100644 index 00000000000000..0e616df897958d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_vr_comfort_2125_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_vr_comfort_2125_pipeline pipeline BertForSequenceClassification from jasonsheih +author: John Snow Labs +name: bert_base_uncased_finetuned_vr_comfort_2125_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_vr_comfort_2125_pipeline` is a English model originally trained by jasonsheih. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_vr_comfort_2125_pipeline_en_5.5.0_3.0_1727381998040.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_vr_comfort_2125_pipeline_en_5.5.0_3.0_1727381998040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_vr_comfort_2125_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_vr_comfort_2125_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_vr_comfort_2125_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jasonsheih/bert-base-uncased-finetuned-vr-comfort-2125 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_wnli_sujatha2502_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_wnli_sujatha2502_pipeline_en.md new file mode 100644 index 00000000000000..89a161ee129aaa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_finetuned_wnli_sujatha2502_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_wnli_sujatha2502_pipeline pipeline BertForSequenceClassification from sujatha2502 +author: John Snow Labs +name: bert_base_uncased_finetuned_wnli_sujatha2502_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_wnli_sujatha2502_pipeline` is a English model originally trained by sujatha2502. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_wnli_sujatha2502_pipeline_en_5.5.0_3.0_1727319917320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_wnli_sujatha2502_pipeline_en_5.5.0_3.0_1727319917320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_wnli_sujatha2502_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_wnli_sujatha2502_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_wnli_sujatha2502_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sujatha2502/bert-base-uncased-finetuned-wnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ft_google_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ft_google_pipeline_en.md new file mode 100644 index 00000000000000..7792c3bbbcd515 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ft_google_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_ft_google_pipeline pipeline BertForSequenceClassification from MatFil99 +author: John Snow Labs +name: bert_base_uncased_ft_google_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ft_google_pipeline` is a English model originally trained by MatFil99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ft_google_pipeline_en_5.5.0_3.0_1727317647158.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ft_google_pipeline_en_5.5.0_3.0_1727317647158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_ft_google_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_ft_google_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ft_google_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MatFil99/bert-base-uncased-ft-google + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_glue_mrpc_santis2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_glue_mrpc_santis2_en.md new file mode 100644 index 00000000000000..f02bf189e23a01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_glue_mrpc_santis2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_glue_mrpc_santis2 BertForSequenceClassification from santis2 +author: John Snow Labs +name: bert_base_uncased_glue_mrpc_santis2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_glue_mrpc_santis2` is a English model originally trained by santis2. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_glue_mrpc_santis2_en_5.5.0_3.0_1727377053220.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_glue_mrpc_santis2_en_5.5.0_3.0_1727377053220.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_base_uncased_glue_mrpc_santis2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_glue_mrpc_santis2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_glue_mrpc_santis2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/santis2/bert-base-uncased-glue-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_grouped_zeroshot_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_grouped_zeroshot_en.md new file mode 100644 index 00000000000000..e181abea1f0563 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_grouped_zeroshot_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_grouped_zeroshot BertForSequenceClassification from kaanakdeniz +author: John Snow Labs +name: bert_base_uncased_grouped_zeroshot +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_grouped_zeroshot` is a English model originally trained by kaanakdeniz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_grouped_zeroshot_en_5.5.0_3.0_1727387665607.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_grouped_zeroshot_en_5.5.0_3.0_1727387665607.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_base_uncased_grouped_zeroshot","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_grouped_zeroshot", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_grouped_zeroshot| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kaanakdeniz/bert_base_uncased_grouped_zeroshot \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_header_plus_textsim_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_header_plus_textsim_en.md new file mode 100644 index 00000000000000..2ca79cd26634af --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_header_plus_textsim_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_header_plus_textsim BertForSequenceClassification from kaanakdeniz +author: John Snow Labs +name: bert_base_uncased_header_plus_textsim +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_header_plus_textsim` is a English model originally trained by kaanakdeniz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_header_plus_textsim_en_5.5.0_3.0_1727350024517.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_header_plus_textsim_en_5.5.0_3.0_1727350024517.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_base_uncased_header_plus_textsim","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_header_plus_textsim", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_header_plus_textsim| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kaanakdeniz/bert_base_uncased_header_plus_textsim \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_hoax_classifier_v3_defs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_hoax_classifier_v3_defs_pipeline_en.md new file mode 100644 index 00000000000000..7f4c38e64deb17 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_hoax_classifier_v3_defs_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_hoax_classifier_v3_defs_pipeline pipeline BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_uncased_hoax_classifier_v3_defs_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_hoax_classifier_v3_defs_pipeline` 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_v3_defs_pipeline_en_5.5.0_3.0_1727349131834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_hoax_classifier_v3_defs_pipeline_en_5.5.0_3.0_1727349131834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_hoax_classifier_v3_defs_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_hoax_classifier_v3_defs_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_hoax_classifier_v3_defs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/research-dump/bert-base-uncased_hoax_classifier_v3_defs + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_en.md new file mode 100644 index 00000000000000..36d744458694d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016 BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ibm_argq_30k_finetuned_convincingness_acl2016` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_en_5.5.0_3.0_1727382612531.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_en_5.5.0_3.0_1727382612531.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_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline_en.md new file mode 100644 index 00000000000000..c4279226c71a95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline pipeline BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline_en_5.5.0_3.0_1727382634829.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline_en_5.5.0_3.0_1727382634829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ibm_argq_30k_finetuned_convincingness_acl2016_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline_en.md new file mode 100644 index 00000000000000..7bcf2d09745507 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline pipeline BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline_en_5.5.0_3.0_1727383141312.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline_en_5.5.0_3.0_1727383141312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ibm_argq_30k_finetuned_sufficiency_ukp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-IBM-argQ-30k-finetuned-sufficiency-ukp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_legal_ic_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_legal_ic_en.md new file mode 100644 index 00000000000000..7c80a6dd17be48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_legal_ic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_legal_ic BertForSequenceClassification from mb7419 +author: John Snow Labs +name: bert_base_uncased_legal_ic +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_legal_ic` is a English model originally trained by mb7419. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_legal_ic_en_5.5.0_3.0_1727377053905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_legal_ic_en_5.5.0_3.0_1727377053905.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_base_uncased_legal_ic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_legal_ic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_legal_ic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/mb7419/bert-base-uncased-legal-ic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_legal_ic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_legal_ic_pipeline_en.md new file mode 100644 index 00000000000000..a0c5ac9fddea8d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_legal_ic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_legal_ic_pipeline pipeline BertForSequenceClassification from mb7419 +author: John Snow Labs +name: bert_base_uncased_legal_ic_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_legal_ic_pipeline` is a English model originally trained by mb7419. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_legal_ic_pipeline_en_5.5.0_3.0_1727377080672.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_legal_ic_pipeline_en_5.5.0_3.0_1727377080672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_legal_ic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_legal_ic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_legal_ic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.8 MB| + +## References + +https://huggingface.co/mb7419/bert-base-uncased-legal-ic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_md_gender_bias_trained_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_md_gender_bias_trained_en.md new file mode 100644 index 00000000000000..729f80d423ae9f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_md_gender_bias_trained_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_md_gender_bias_trained BertForSequenceClassification from JakobKaiser +author: John Snow Labs +name: bert_base_uncased_md_gender_bias_trained +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_md_gender_bias_trained` is a English model originally trained by JakobKaiser. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_md_gender_bias_trained_en_5.5.0_3.0_1727380798924.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_md_gender_bias_trained_en_5.5.0_3.0_1727380798924.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_base_uncased_md_gender_bias_trained","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_md_gender_bias_trained", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_md_gender_bias_trained| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JakobKaiser/bert-base-uncased-md_gender_bias-trained \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_mean_pooling_finetuned3_cola_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_mean_pooling_finetuned3_cola_en.md new file mode 100644 index 00000000000000..12dbe195e09e5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_mean_pooling_finetuned3_cola_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_mean_pooling_finetuned3_cola BertForSequenceClassification from ilkekas +author: John Snow Labs +name: bert_base_uncased_mean_pooling_finetuned3_cola +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mean_pooling_finetuned3_cola` is a English model originally trained by ilkekas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mean_pooling_finetuned3_cola_en_5.5.0_3.0_1727385874176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mean_pooling_finetuned3_cola_en_5.5.0_3.0_1727385874176.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_base_uncased_mean_pooling_finetuned3_cola","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mean_pooling_finetuned3_cola", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mean_pooling_finetuned3_cola| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ilkekas/bert-base-uncased-mean-pooling-finetuned3-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_news_about_gold_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_news_about_gold_pipeline_en.md new file mode 100644 index 00000000000000..523e751c319f2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_news_about_gold_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_news_about_gold_pipeline pipeline BertForSequenceClassification from DunnBC22 +author: John Snow Labs +name: bert_base_uncased_news_about_gold_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_news_about_gold_pipeline` is a English model originally trained by DunnBC22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_news_about_gold_pipeline_en_5.5.0_3.0_1727346485849.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_news_about_gold_pipeline_en_5.5.0_3.0_1727346485849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_news_about_gold_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_news_about_gold_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_news_about_gold_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DunnBC22/bert-base-uncased-News_About_Gold + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_offenseval2019_upsample_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_offenseval2019_upsample_en.md new file mode 100644 index 00000000000000..658da6c8d87318 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_offenseval2019_upsample_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_offenseval2019_upsample BertForSequenceClassification from mohsenfayyaz +author: John Snow Labs +name: bert_base_uncased_offenseval2019_upsample +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_offenseval2019_upsample` is a English model originally trained by mohsenfayyaz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_offenseval2019_upsample_en_5.5.0_3.0_1727371095968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_offenseval2019_upsample_en_5.5.0_3.0_1727371095968.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_base_uncased_offenseval2019_upsample","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_offenseval2019_upsample", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_offenseval2019_upsample| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mohsenfayyaz/bert-base-uncased-offenseval2019-upsample \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_offenseval2019_upsample_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_offenseval2019_upsample_pipeline_en.md new file mode 100644 index 00000000000000..b0e6981fc781f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_offenseval2019_upsample_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_offenseval2019_upsample_pipeline pipeline BertForSequenceClassification from mohsenfayyaz +author: John Snow Labs +name: bert_base_uncased_offenseval2019_upsample_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_offenseval2019_upsample_pipeline` is a English model originally trained by mohsenfayyaz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_offenseval2019_upsample_pipeline_en_5.5.0_3.0_1727371117123.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_offenseval2019_upsample_pipeline_en_5.5.0_3.0_1727371117123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_offenseval2019_upsample_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_offenseval2019_upsample_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_offenseval2019_upsample_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mohsenfayyaz/bert-base-uncased-offenseval2019-upsample + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_paradetox_with_labels_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_paradetox_with_labels_pipeline_en.md new file mode 100644 index 00000000000000..98150a2d20ed4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_paradetox_with_labels_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_paradetox_with_labels_pipeline pipeline BertForSequenceClassification from HamdanXI +author: John Snow Labs +name: bert_base_uncased_paradetox_with_labels_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_paradetox_with_labels_pipeline` is a English model originally trained by HamdanXI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_paradetox_with_labels_pipeline_en_5.5.0_3.0_1727341039417.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_paradetox_with_labels_pipeline_en_5.5.0_3.0_1727341039417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_paradetox_with_labels_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_paradetox_with_labels_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_paradetox_with_labels_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/HamdanXI/bert-base-uncased-paradetox_with_labels + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_qnli_epochs_2_lr_5e_05_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_qnli_epochs_2_lr_5e_05_en.md new file mode 100644 index 00000000000000..3cf14571c44291 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_qnli_epochs_2_lr_5e_05_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_qnli_epochs_2_lr_5e_05 BertForSequenceClassification from prateeky2806 +author: John Snow Labs +name: bert_base_uncased_qnli_epochs_2_lr_5e_05 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_epochs_2_lr_5e_05` is a English model originally trained by prateeky2806. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qnli_epochs_2_lr_5e_05_en_5.5.0_3.0_1727370072300.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qnli_epochs_2_lr_5e_05_en_5.5.0_3.0_1727370072300.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_base_uncased_qnli_epochs_2_lr_5e_05","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qnli_epochs_2_lr_5e_05", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_qnli_epochs_2_lr_5e_05| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/prateeky2806/bert-base-uncased-qnli-epochs-2-lr-5e-05 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline_en.md new file mode 100644 index 00000000000000..fca42bac032a24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline pipeline BertForSequenceClassification from yoshitomo-matsubara +author: John Snow Labs +name: bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline` is a English model originally trained by yoshitomo-matsubara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline_en_5.5.0_3.0_1727372483573.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline_en_5.5.0_3.0_1727372483573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_qqp_from_bert_large_uncased_qqp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yoshitomo-matsubara/bert-base-uncased-qqp_from_bert-large-uncased-qqp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_relevance_extractor_secondary_binary_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_relevance_extractor_secondary_binary_en.md new file mode 100644 index 00000000000000..7b23af63940927 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_relevance_extractor_secondary_binary_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_relevance_extractor_secondary_binary BertForSequenceClassification from liy140 +author: John Snow Labs +name: bert_base_uncased_relevance_extractor_secondary_binary +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_relevance_extractor_secondary_binary` is a English model originally trained by liy140. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_relevance_extractor_secondary_binary_en_5.5.0_3.0_1727372053620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_relevance_extractor_secondary_binary_en_5.5.0_3.0_1727372053620.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_base_uncased_relevance_extractor_secondary_binary","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_relevance_extractor_secondary_binary", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_relevance_extractor_secondary_binary| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/liy140/bert-base-uncased_relevance_extractor_secondary_binary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_relevance_extractor_secondary_binary_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_relevance_extractor_secondary_binary_pipeline_en.md new file mode 100644 index 00000000000000..ea015b8c9e6f74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_relevance_extractor_secondary_binary_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_relevance_extractor_secondary_binary_pipeline pipeline BertForSequenceClassification from liy140 +author: John Snow Labs +name: bert_base_uncased_relevance_extractor_secondary_binary_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_relevance_extractor_secondary_binary_pipeline` is a English model originally trained by liy140. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_relevance_extractor_secondary_binary_pipeline_en_5.5.0_3.0_1727372075879.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_relevance_extractor_secondary_binary_pipeline_en_5.5.0_3.0_1727372075879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_relevance_extractor_secondary_binary_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_relevance_extractor_secondary_binary_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_relevance_extractor_secondary_binary_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/liy140/bert-base-uncased_relevance_extractor_secondary_binary + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_resume_screening_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_resume_screening_en.md new file mode 100644 index 00000000000000..070505fc164918 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_resume_screening_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_resume_screening BertForSequenceClassification from MScDS2023 +author: John Snow Labs +name: bert_base_uncased_resume_screening +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_resume_screening` is a English model originally trained by MScDS2023. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_resume_screening_en_5.5.0_3.0_1727379232990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_resume_screening_en_5.5.0_3.0_1727379232990.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_base_uncased_resume_screening","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_resume_screening", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_resume_screening| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MScDS2023/bert-base-uncased-resume-screening \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_resume_screening_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_resume_screening_pipeline_en.md new file mode 100644 index 00000000000000..454bb3ffa2f7f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_resume_screening_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_resume_screening_pipeline pipeline BertForSequenceClassification from MScDS2023 +author: John Snow Labs +name: bert_base_uncased_resume_screening_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_resume_screening_pipeline` is a English model originally trained by MScDS2023. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_resume_screening_pipeline_en_5.5.0_3.0_1727379255934.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_resume_screening_pipeline_en_5.5.0_3.0_1727379255934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_resume_screening_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_resume_screening_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_resume_screening_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MScDS2023/bert-base-uncased-resume-screening + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_sst2_kowsiknd_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_sst2_kowsiknd_pipeline_en.md new file mode 100644 index 00000000000000..000c0b10d01039 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_sst2_kowsiknd_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_sst2_kowsiknd_pipeline pipeline BertForSequenceClassification from kowsiknd +author: John Snow Labs +name: bert_base_uncased_sst2_kowsiknd_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst2_kowsiknd_pipeline` is a English model originally trained by kowsiknd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_kowsiknd_pipeline_en_5.5.0_3.0_1727348858949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_kowsiknd_pipeline_en_5.5.0_3.0_1727348858949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_sst2_kowsiknd_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_sst2_kowsiknd_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst2_kowsiknd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kowsiknd/bert-base-uncased-sst2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tesla_ic_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tesla_ic_en.md new file mode 100644 index 00000000000000..3773172fd587dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tesla_ic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_tesla_ic BertForSequenceClassification from mb7419 +author: John Snow Labs +name: bert_base_uncased_tesla_ic +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_tesla_ic` is a English model originally trained by mb7419. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tesla_ic_en_5.5.0_3.0_1727385854368.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tesla_ic_en_5.5.0_3.0_1727385854368.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_base_uncased_tesla_ic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_tesla_ic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_tesla_ic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/mb7419/bert-base-uncased-tesla-ic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tesla_ic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tesla_ic_pipeline_en.md new file mode 100644 index 00000000000000..3376486b3efde9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tesla_ic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_tesla_ic_pipeline pipeline BertForSequenceClassification from mb7419 +author: John Snow Labs +name: bert_base_uncased_tesla_ic_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_tesla_ic_pipeline` is a English model originally trained by mb7419. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tesla_ic_pipeline_en_5.5.0_3.0_1727385875669.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tesla_ic_pipeline_en_5.5.0_3.0_1727385875669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_tesla_ic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_tesla_ic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_tesla_ic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/mb7419/bert-base-uncased-tesla-ic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_textcls_rheology_20230912_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_textcls_rheology_20230912_pipeline_en.md new file mode 100644 index 00000000000000..f38b20ee56f08c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_textcls_rheology_20230912_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_textcls_rheology_20230912_pipeline pipeline BertForSequenceClassification from jonas-luehrs +author: John Snow Labs +name: bert_base_uncased_textcls_rheology_20230912_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_textcls_rheology_20230912_pipeline` is a English model originally trained by jonas-luehrs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_textcls_rheology_20230912_pipeline_en_5.5.0_3.0_1727370227270.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_textcls_rheology_20230912_pipeline_en_5.5.0_3.0_1727370227270.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_textcls_rheology_20230912_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_textcls_rheology_20230912_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_textcls_rheology_20230912_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jonas-luehrs/bert-base-uncased-textCLS-RHEOLOGY-20230912 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tminer_hs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tminer_hs_pipeline_en.md new file mode 100644 index 00000000000000..06fe4189dac70b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_tminer_hs_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_tminer_hs_pipeline pipeline BertForSequenceClassification from nealmgkr +author: John Snow Labs +name: bert_base_uncased_tminer_hs_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_tminer_hs_pipeline` is a English model originally trained by nealmgkr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tminer_hs_pipeline_en_5.5.0_3.0_1727311430862.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_tminer_hs_pipeline_en_5.5.0_3.0_1727311430862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_tminer_hs_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_tminer_hs_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_tminer_hs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/nealmgkr/bert-base-uncased-tminer-hs + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_top_pruned_qqp_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_top_pruned_qqp_en.md new file mode 100644 index 00000000000000..07a8b8452cd717 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_top_pruned_qqp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_top_pruned_qqp BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_top_pruned_qqp +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_top_pruned_qqp` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_top_pruned_qqp_en_5.5.0_3.0_1727355991966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_top_pruned_qqp_en_5.5.0_3.0_1727355991966.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_base_uncased_top_pruned_qqp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_top_pruned_qqp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_top_pruned_qqp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-top-pruned-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_v1_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_v1_en.md new file mode 100644 index 00000000000000..b0c5ae9c588a3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_base_uncased_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_v1 BertForSequenceClassification from echoquery +author: John Snow Labs +name: bert_base_uncased_v1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_v1` is a English model originally trained by echoquery. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_v1_en_5.5.0_3.0_1727318529847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_v1_en_5.5.0_3.0_1727318529847.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_base_uncased_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/echoquery/bert-base-uncased-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_classification_emotion_persian_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_classification_emotion_persian_en.md new file mode 100644 index 00000000000000..53e176bb4fe8a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_classification_emotion_persian_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_classification_emotion_persian BertForSequenceClassification from Mohammdrezasajjadi +author: John Snow Labs +name: bert_classification_emotion_persian +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_emotion_persian` is a English model originally trained by Mohammdrezasajjadi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classification_emotion_persian_en_5.5.0_3.0_1727372078828.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classification_emotion_persian_en_5.5.0_3.0_1727372078828.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_classification_emotion_persian","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_emotion_persian", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classification_emotion_persian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|608.7 MB| + +## References + +https://huggingface.co/Mohammdrezasajjadi/bert_classification_emotion_persian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_classification_emotion_persian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_classification_emotion_persian_pipeline_en.md new file mode 100644 index 00000000000000..39f207168288d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_classification_emotion_persian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_classification_emotion_persian_pipeline pipeline BertForSequenceClassification from Mohammdrezasajjadi +author: John Snow Labs +name: bert_classification_emotion_persian_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classification_emotion_persian_pipeline` is a English model originally trained by Mohammdrezasajjadi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classification_emotion_persian_pipeline_en_5.5.0_3.0_1727372115527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classification_emotion_persian_pipeline_en_5.5.0_3.0_1727372115527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classification_emotion_persian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classification_emotion_persian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classification_emotion_persian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|608.7 MB| + +## References + +https://huggingface.co/Mohammdrezasajjadi/bert_classification_emotion_persian + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_drug_review_tonga_tonga_islands_condition_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_drug_review_tonga_tonga_islands_condition_en.md new file mode 100644 index 00000000000000..ce8efc07577db7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_drug_review_tonga_tonga_islands_condition_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_drug_review_tonga_tonga_islands_condition BertForSequenceClassification from Marcuswas +author: John Snow Labs +name: bert_drug_review_tonga_tonga_islands_condition +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_drug_review_tonga_tonga_islands_condition` is a English model originally trained by Marcuswas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_drug_review_tonga_tonga_islands_condition_en_5.5.0_3.0_1727368708349.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_drug_review_tonga_tonga_islands_condition_en_5.5.0_3.0_1727368708349.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_drug_review_tonga_tonga_islands_condition","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_drug_review_tonga_tonga_islands_condition", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_drug_review_tonga_tonga_islands_condition| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/Marcuswas/bert-drug-review-to-condition \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_drug_review_tonga_tonga_islands_condition_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_drug_review_tonga_tonga_islands_condition_pipeline_en.md new file mode 100644 index 00000000000000..384e8b0aad43a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_drug_review_tonga_tonga_islands_condition_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_drug_review_tonga_tonga_islands_condition_pipeline pipeline BertForSequenceClassification from Marcuswas +author: John Snow Labs +name: bert_drug_review_tonga_tonga_islands_condition_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_drug_review_tonga_tonga_islands_condition_pipeline` is a English model originally trained by Marcuswas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_drug_review_tonga_tonga_islands_condition_pipeline_en_5.5.0_3.0_1727368729975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_drug_review_tonga_tonga_islands_condition_pipeline_en_5.5.0_3.0_1727368729975.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_drug_review_tonga_tonga_islands_condition_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_drug_review_tonga_tonga_islands_condition_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_drug_review_tonga_tonga_islands_condition_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/Marcuswas/bert-drug-review-to-condition + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_fine_tuned_cola_pallavi176_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_fine_tuned_cola_pallavi176_pipeline_en.md new file mode 100644 index 00000000000000..b3ed227f2bd0b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_fine_tuned_cola_pallavi176_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_fine_tuned_cola_pallavi176_pipeline pipeline BertForSequenceClassification from pallavi176 +author: John Snow Labs +name: bert_fine_tuned_cola_pallavi176_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_cola_pallavi176_pipeline` is a English model originally trained by pallavi176. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_pallavi176_pipeline_en_5.5.0_3.0_1727315331081.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_pallavi176_pipeline_en_5.5.0_3.0_1727315331081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_fine_tuned_cola_pallavi176_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_fine_tuned_cola_pallavi176_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_cola_pallavi176_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/pallavi176/bert-fine-tuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_math_prob_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_math_prob_classification_pipeline_en.md new file mode 100644 index 00000000000000..6f638f7a520096 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_math_prob_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_math_prob_classification_pipeline pipeline BertForSequenceClassification from lschlessinger +author: John Snow Labs +name: bert_finetuned_math_prob_classification_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_math_prob_classification_pipeline` is a English model originally trained by lschlessinger. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_math_prob_classification_pipeline_en_5.5.0_3.0_1727348056815.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_math_prob_classification_pipeline_en_5.5.0_3.0_1727348056815.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_math_prob_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_math_prob_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_math_prob_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/lschlessinger/bert-finetuned-math-prob-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_mrpc_jkassemi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_mrpc_jkassemi_pipeline_en.md new file mode 100644 index 00000000000000..39a3cd2af32a88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_mrpc_jkassemi_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_mrpc_jkassemi_pipeline pipeline BertForSequenceClassification from jkassemi +author: John Snow Labs +name: bert_finetuned_mrpc_jkassemi_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_mrpc_jkassemi_pipeline` is a English model originally trained by jkassemi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_jkassemi_pipeline_en_5.5.0_3.0_1727351513849.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_jkassemi_pipeline_en_5.5.0_3.0_1727351513849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_mrpc_jkassemi_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_mrpc_jkassemi_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_mrpc_jkassemi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jkassemi/bert-finetuned-mrpc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_mrpc_simtaewan_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_mrpc_simtaewan_pipeline_en.md new file mode 100644 index 00000000000000..baa2692ee83d37 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_mrpc_simtaewan_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_mrpc_simtaewan_pipeline pipeline BertForSequenceClassification from Simtaewan +author: John Snow Labs +name: bert_finetuned_mrpc_simtaewan_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_mrpc_simtaewan_pipeline` is a English model originally trained by Simtaewan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_simtaewan_pipeline_en_5.5.0_3.0_1727317646413.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_simtaewan_pipeline_en_5.5.0_3.0_1727317646413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_mrpc_simtaewan_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_mrpc_simtaewan_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_mrpc_simtaewan_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Simtaewan/bert-finetuned-mrpc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_semitic_languages_eval_english_balluk_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_semitic_languages_eval_english_balluk_en.md new file mode 100644 index 00000000000000..772a4575c63560 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_semitic_languages_eval_english_balluk_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_semitic_languages_eval_english_balluk BertForSequenceClassification from balluk +author: John Snow Labs +name: bert_finetuned_semitic_languages_eval_english_balluk +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_semitic_languages_eval_english_balluk` is a English model originally trained by balluk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_semitic_languages_eval_english_balluk_en_5.5.0_3.0_1727310867952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_semitic_languages_eval_english_balluk_en_5.5.0_3.0_1727310867952.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_finetuned_semitic_languages_eval_english_balluk","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_semitic_languages_eval_english_balluk", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_semitic_languages_eval_english_balluk| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/balluk/bert-finetuned-sem_eval-english \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_semitic_languages_eval_english_yangel88_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_semitic_languages_eval_english_yangel88_pipeline_en.md new file mode 100644 index 00000000000000..06dc728d28e78d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_semitic_languages_eval_english_yangel88_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_semitic_languages_eval_english_yangel88_pipeline pipeline BertForSequenceClassification from yangel88 +author: John Snow Labs +name: bert_finetuned_semitic_languages_eval_english_yangel88_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_semitic_languages_eval_english_yangel88_pipeline` is a English model originally trained by yangel88. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_semitic_languages_eval_english_yangel88_pipeline_en_5.5.0_3.0_1727318743244.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_semitic_languages_eval_english_yangel88_pipeline_en_5.5.0_3.0_1727318743244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_semitic_languages_eval_english_yangel88_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_semitic_languages_eval_english_yangel88_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_semitic_languages_eval_english_yangel88_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yangel88/bert-finetuned-sem_eval-english + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_vashesh_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_vashesh_en.md new file mode 100644 index 00000000000000..f9345063c77b4c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_vashesh_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_vashesh BertForSequenceClassification from Vashesh +author: John Snow Labs +name: bert_finetuned_vashesh +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_vashesh` is a English model originally trained by Vashesh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_vashesh_en_5.5.0_3.0_1727379616416.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_vashesh_en_5.5.0_3.0_1727379616416.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_finetuned_vashesh","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_vashesh", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_vashesh| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|406.5 MB| + +## References + +https://huggingface.co/Vashesh/Bert_Finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_vashesh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_vashesh_pipeline_en.md new file mode 100644 index 00000000000000..adc8bdc92c4a2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuned_vashesh_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_vashesh_pipeline pipeline BertForSequenceClassification from Vashesh +author: John Snow Labs +name: bert_finetuned_vashesh_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_vashesh_pipeline` is a English model originally trained by Vashesh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_vashesh_pipeline_en_5.5.0_3.0_1727379641488.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_vashesh_pipeline_en_5.5.0_3.0_1727379641488.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_vashesh_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_vashesh_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_vashesh_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.5 MB| + +## References + +https://huggingface.co/Vashesh/Bert_Finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_finetuning_test_liangxiaoxiao_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuning_test_liangxiaoxiao_pipeline_en.md new file mode 100644 index 00000000000000..c60136d8f10bf8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_finetuning_test_liangxiaoxiao_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuning_test_liangxiaoxiao_pipeline pipeline BertForSequenceClassification from liangxiaoxiao +author: John Snow Labs +name: bert_finetuning_test_liangxiaoxiao_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuning_test_liangxiaoxiao_pipeline` is a English model originally trained by liangxiaoxiao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_liangxiaoxiao_pipeline_en_5.5.0_3.0_1727315207927.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_liangxiaoxiao_pipeline_en_5.5.0_3.0_1727315207927.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuning_test_liangxiaoxiao_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuning_test_liangxiaoxiao_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuning_test_liangxiaoxiao_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/liangxiaoxiao/bert_finetuning_test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_ft_cola_41_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_ft_cola_41_pipeline_en.md new file mode 100644 index 00000000000000..46110261b56b71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_ft_cola_41_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_ft_cola_41_pipeline pipeline BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_41_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_41_pipeline` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_41_pipeline_en_5.5.0_3.0_1727377330577.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_41_pipeline_en_5.5.0_3.0_1727377330577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_ft_cola_41_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_ft_cola_41_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_41_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-41 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_labr_unbalanced_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-26-bert_labr_unbalanced_pipeline_ar.md new file mode 100644 index 00000000000000..132dc32e1a39bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_labr_unbalanced_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic bert_labr_unbalanced_pipeline pipeline BertForSequenceClassification from mofawzy +author: John Snow Labs +name: bert_labr_unbalanced_pipeline +date: 2024-09-26 +tags: [ar, open_source, pipeline, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_labr_unbalanced_pipeline` is a Arabic model originally trained by mofawzy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_labr_unbalanced_pipeline_ar_5.5.0_3.0_1727380840591.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_labr_unbalanced_pipeline_ar_5.5.0_3.0_1727380840591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_labr_unbalanced_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_labr_unbalanced_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_labr_unbalanced_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|1.3 GB| + +## References + +https://huggingface.co/mofawzy/bert-labr-unbalanced + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_cased_mnli_model3_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_cased_mnli_model3_en.md new file mode 100644 index 00000000000000..461aa136b9f3ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_cased_mnli_model3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_cased_mnli_model3 BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_large_cased_mnli_model3 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mnli_model3` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_mnli_model3_en_5.5.0_3.0_1727377277600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_mnli_model3_en_5.5.0_3.0_1727377277600.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_large_cased_mnli_model3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_cased_mnli_model3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_mnli_model3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/varun-v-rao/bert-large-cased-mnli-model3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_cased_mnli_model3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_cased_mnli_model3_pipeline_en.md new file mode 100644 index 00000000000000..f5f05a5f9b6f9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_cased_mnli_model3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_cased_mnli_model3_pipeline pipeline BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_large_cased_mnli_model3_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_mnli_model3_pipeline` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_mnli_model3_pipeline_en_5.5.0_3.0_1727377343036.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_mnli_model3_pipeline_en_5.5.0_3.0_1727377343036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_cased_mnli_model3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_cased_mnli_model3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_mnli_model3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/varun-v-rao/bert-large-cased-mnli-model3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_finetuned_phishing_webpage_version_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_finetuned_phishing_webpage_version_en.md new file mode 100644 index 00000000000000..5d559220e6e41c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_finetuned_phishing_webpage_version_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_finetuned_phishing_webpage_version BertForSequenceClassification from huynq3Cyradar +author: John Snow Labs +name: bert_large_finetuned_phishing_webpage_version +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_finetuned_phishing_webpage_version` is a English model originally trained by huynq3Cyradar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_webpage_version_en_5.5.0_3.0_1727382033870.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_webpage_version_en_5.5.0_3.0_1727382033870.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_large_finetuned_phishing_webpage_version","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_finetuned_phishing_webpage_version", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_finetuned_phishing_webpage_version| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/huynq3Cyradar/bert-large-finetuned-phishing-webpage-version \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_finetuned_phishing_webpage_version_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_finetuned_phishing_webpage_version_pipeline_en.md new file mode 100644 index 00000000000000..bfbe0dd7a04da3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_finetuned_phishing_webpage_version_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_finetuned_phishing_webpage_version_pipeline pipeline BertForSequenceClassification from huynq3Cyradar +author: John Snow Labs +name: bert_large_finetuned_phishing_webpage_version_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_finetuned_phishing_webpage_version_pipeline` is a English model originally trained by huynq3Cyradar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_webpage_version_pipeline_en_5.5.0_3.0_1727382070351.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_webpage_version_pipeline_en_5.5.0_3.0_1727382070351.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_finetuned_phishing_webpage_version_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_finetuned_phishing_webpage_version_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_finetuned_phishing_webpage_version_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/huynq3Cyradar/bert-large-finetuned-phishing-webpage-version + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_cree_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_cree_en.md new file mode 100644 index 00000000000000..274e0b7d39a8c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_cree_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_uncased_cls_cree BertForSequenceClassification from ghatgetanuj +author: John Snow Labs +name: bert_large_uncased_cls_cree +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_cls_cree` is a English model originally trained by ghatgetanuj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cls_cree_en_5.5.0_3.0_1727380424930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cls_cree_en_5.5.0_3.0_1727380424930.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_large_uncased_cls_cree","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_cls_cree", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_cls_cree| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ghatgetanuj/bert-large-uncased_cls_CR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_cree_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_cree_pipeline_en.md new file mode 100644 index 00000000000000..baedfd0eea7c60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_cree_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_uncased_cls_cree_pipeline pipeline BertForSequenceClassification from ghatgetanuj +author: John Snow Labs +name: bert_large_uncased_cls_cree_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_cls_cree_pipeline` is a English model originally trained by ghatgetanuj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cls_cree_pipeline_en_5.5.0_3.0_1727380493959.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cls_cree_pipeline_en_5.5.0_3.0_1727380493959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_uncased_cls_cree_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_uncased_cls_cree_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_cls_cree_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ghatgetanuj/bert-large-uncased_cls_CR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_subj_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_subj_en.md new file mode 100644 index 00000000000000..265eca805bff0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_subj_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_uncased_cls_subj BertForSequenceClassification from ghatgetanuj +author: John Snow Labs +name: bert_large_uncased_cls_subj +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_cls_subj` is a English model originally trained by ghatgetanuj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cls_subj_en_5.5.0_3.0_1727373034562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cls_subj_en_5.5.0_3.0_1727373034562.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_large_uncased_cls_subj","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_cls_subj", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_cls_subj| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ghatgetanuj/bert-large-uncased_cls_subj \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_subj_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_subj_pipeline_en.md new file mode 100644 index 00000000000000..d79a40055fe0df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_cls_subj_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_uncased_cls_subj_pipeline pipeline BertForSequenceClassification from ghatgetanuj +author: John Snow Labs +name: bert_large_uncased_cls_subj_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_cls_subj_pipeline` is a English model originally trained by ghatgetanuj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cls_subj_pipeline_en_5.5.0_3.0_1727373096656.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cls_subj_pipeline_en_5.5.0_3.0_1727373096656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_uncased_cls_subj_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_uncased_cls_subj_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_cls_subj_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ghatgetanuj/bert-large-uncased_cls_subj + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_hate_offensive_normal_speech_lr_2e_05_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_hate_offensive_normal_speech_lr_2e_05_en.md new file mode 100644 index 00000000000000..23256e532e3e94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_hate_offensive_normal_speech_lr_2e_05_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_uncased_hate_offensive_normal_speech_lr_2e_05 BertForSequenceClassification from DrishtiSharma +author: John Snow Labs +name: bert_large_uncased_hate_offensive_normal_speech_lr_2e_05 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_hate_offensive_normal_speech_lr_2e_05` is a English model originally trained by DrishtiSharma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_hate_offensive_normal_speech_lr_2e_05_en_5.5.0_3.0_1727381031190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_hate_offensive_normal_speech_lr_2e_05_en_5.5.0_3.0_1727381031190.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_large_uncased_hate_offensive_normal_speech_lr_2e_05","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_hate_offensive_normal_speech_lr_2e_05", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_hate_offensive_normal_speech_lr_2e_05| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/DrishtiSharma/bert-large-uncased-hate-offensive-normal-speech-lr-2e-05 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_mnli_en.md new file mode 100644 index 00000000000000..85864277622d10 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_mnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_uncased_mnli BertForSequenceClassification from madlag +author: John Snow Labs +name: bert_large_uncased_mnli +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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` is a English model originally trained by madlag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_mnli_en_5.5.0_3.0_1727381414510.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_mnli_en_5.5.0_3.0_1727381414510.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_large_uncased_mnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_mnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_mnli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/madlag/bert-large-uncased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_mnli_pipeline_en.md new file mode 100644 index 00000000000000..c6bfe60d9c84fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_mnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_uncased_mnli_pipeline pipeline BertForSequenceClassification from madlag +author: John Snow Labs +name: bert_large_uncased_mnli_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_mnli_pipeline` is a English model originally trained by madlag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_mnli_pipeline_en_5.5.0_3.0_1727381481052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_mnli_pipeline_en_5.5.0_3.0_1727381481052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_uncased_mnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_uncased_mnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_mnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/madlag/bert-large-uncased-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_sentiment_en.md new file mode 100644 index 00000000000000..9f8b5cf5234445 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_large_uncased_sentiment_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_uncased_sentiment BertForSequenceClassification from rttl-ai +author: John Snow Labs +name: bert_large_uncased_sentiment +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sentiment` is a English model originally trained by rttl-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sentiment_en_5.5.0_3.0_1727324169337.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sentiment_en_5.5.0_3.0_1727324169337.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_large_uncased_sentiment","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sentiment", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sentiment| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/rttl-ai/bert-large-uncased-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_mdgender_convai_ternary_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_mdgender_convai_ternary_en.md new file mode 100644 index 00000000000000..688acb85453186 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_mdgender_convai_ternary_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_mdgender_convai_ternary BertForSequenceClassification from Cameron +author: John Snow Labs +name: bert_mdgender_convai_ternary +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mdgender_convai_ternary` is a English model originally trained by Cameron. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mdgender_convai_ternary_en_5.5.0_3.0_1727367228515.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mdgender_convai_ternary_en_5.5.0_3.0_1727367228515.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_mdgender_convai_ternary","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mdgender_convai_ternary", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mdgender_convai_ternary| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Cameron/BERT-mdgender-convai-ternary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_mini_url_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_mini_url_en.md new file mode 100644 index 00000000000000..6d9328061ee718 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_mini_url_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_mini_url BertForSequenceClassification from DenBur +author: John Snow Labs +name: bert_mini_url +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_url` is a English model originally trained by DenBur. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_url_en_5.5.0_3.0_1727378186927.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_url_en_5.5.0_3.0_1727378186927.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_mini_url","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_url", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_url| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/DenBur/bert-mini-url \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_mini_url_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_mini_url_pipeline_en.md new file mode 100644 index 00000000000000..2d19efc633bfe9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_mini_url_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mini_url_pipeline pipeline BertForSequenceClassification from DenBur +author: John Snow Labs +name: bert_mini_url_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_url_pipeline` is a English model originally trained by DenBur. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_url_pipeline_en_5.5.0_3.0_1727378189380.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_url_pipeline_en_5.5.0_3.0_1727378189380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mini_url_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mini_url_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_url_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/DenBur/bert-mini-url + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_mnli_medium_1k_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_mnli_medium_1k_en.md new file mode 100644 index 00000000000000..3b61d10d99e697 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_mnli_medium_1k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_mnli_medium_1k BertForSequenceClassification from Elkelouizajo +author: John Snow Labs +name: bert_mnli_medium_1k +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mnli_medium_1k` is a English model originally trained by Elkelouizajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mnli_medium_1k_en_5.5.0_3.0_1727386332916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mnli_medium_1k_en_5.5.0_3.0_1727386332916.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_mnli_medium_1k","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mnli_medium_1k", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mnli_medium_1k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Elkelouizajo/BERT_mnli_medium_1K \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_mnli_medium_1k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_mnli_medium_1k_pipeline_en.md new file mode 100644 index 00000000000000..88f74f82371285 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_mnli_medium_1k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mnli_medium_1k_pipeline pipeline BertForSequenceClassification from Elkelouizajo +author: John Snow Labs +name: bert_mnli_medium_1k_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mnli_medium_1k_pipeline` is a English model originally trained by Elkelouizajo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mnli_medium_1k_pipeline_en_5.5.0_3.0_1727386398806.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mnli_medium_1k_pipeline_en_5.5.0_3.0_1727386398806.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mnli_medium_1k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mnli_medium_1k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mnli_medium_1k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Elkelouizajo/BERT_mnli_medium_1K + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_mrpc_trained_brundal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_mrpc_trained_brundal_pipeline_en.md new file mode 100644 index 00000000000000..cc0908192df8a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_mrpc_trained_brundal_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mrpc_trained_brundal_pipeline pipeline BertForSequenceClassification from BrundaL +author: John Snow Labs +name: bert_mrpc_trained_brundal_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mrpc_trained_brundal_pipeline` is a English model originally trained by BrundaL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mrpc_trained_brundal_pipeline_en_5.5.0_3.0_1727384412553.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mrpc_trained_brundal_pipeline_en_5.5.0_3.0_1727384412553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mrpc_trained_brundal_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mrpc_trained_brundal_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mrpc_trained_brundal_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/BrundaL/bert_mrpc_trained + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_persian_farsi_base_uncased_sentiment_nlp_hw2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_persian_farsi_base_uncased_sentiment_nlp_hw2_en.md new file mode 100644 index 00000000000000..f89224518fedf0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_persian_farsi_base_uncased_sentiment_nlp_hw2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_persian_farsi_base_uncased_sentiment_nlp_hw2 BertForSequenceClassification from farzanrahmani +author: John Snow Labs +name: bert_persian_farsi_base_uncased_sentiment_nlp_hw2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_persian_farsi_base_uncased_sentiment_nlp_hw2` is a English model originally trained by farzanrahmani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_persian_farsi_base_uncased_sentiment_nlp_hw2_en_5.5.0_3.0_1727323278834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_persian_farsi_base_uncased_sentiment_nlp_hw2_en_5.5.0_3.0_1727323278834.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_persian_farsi_base_uncased_sentiment_nlp_hw2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_persian_farsi_base_uncased_sentiment_nlp_hw2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_persian_farsi_base_uncased_sentiment_nlp_hw2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|608.7 MB| + +## References + +https://huggingface.co/farzanrahmani/bert-fa-base-uncased-sentiment-nlp-hw2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_reviews_chadia_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_reviews_chadia_en.md new file mode 100644 index 00000000000000..93514c7e3017d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_reviews_chadia_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_reviews_chadia BertForSequenceClassification from chadia +author: John Snow Labs +name: bert_reviews_chadia +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_reviews_chadia` is a English model originally trained by chadia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_reviews_chadia_en_5.5.0_3.0_1727343499372.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_reviews_chadia_en_5.5.0_3.0_1727343499372.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_reviews_chadia","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_reviews_chadia", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_reviews_chadia| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/chadia/Bert_reviews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_rte_distilled_cka_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_rte_distilled_cka_pipeline_en.md new file mode 100644 index 00000000000000..172682a9fdc65e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_rte_distilled_cka_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_rte_distilled_cka_pipeline pipeline BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: bert_rte_distilled_cka_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_rte_distilled_cka_pipeline` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_rte_distilled_cka_pipeline_en_5.5.0_3.0_1727312033745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_rte_distilled_cka_pipeline_en_5.5.0_3.0_1727312033745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_rte_distilled_cka_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_rte_distilled_cka_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_rte_distilled_cka_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|155.1 MB| + +## References + +https://huggingface.co/Sayan01/bert-rte-distilled-cka + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_russian_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-26-bert_russian_pipeline_ru.md new file mode 100644 index 00000000000000..06de437cfc0e51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_russian_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian bert_russian_pipeline pipeline BertForSequenceClassification from mikhmanoff +author: John Snow Labs +name: bert_russian_pipeline +date: 2024-09-26 +tags: [ru, open_source, pipeline, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_russian_pipeline` is a Russian model originally trained by mikhmanoff. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_russian_pipeline_ru_5.5.0_3.0_1727385541836.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_russian_pipeline_ru_5.5.0_3.0_1727385541836.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_russian_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_russian_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_russian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|109.5 MB| + +## References + +https://huggingface.co/mikhmanoff/bert_ru + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_russian_ru.md b/docs/_posts/ahmedlone127/2024-09-26-bert_russian_ru.md new file mode 100644 index 00000000000000..98851aea4149e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_russian_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian bert_russian BertForSequenceClassification from mikhmanoff +author: John Snow Labs +name: bert_russian +date: 2024-09-26 +tags: [ru, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_russian` is a Russian model originally trained by mikhmanoff. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_russian_ru_5.5.0_3.0_1727385535882.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_russian_ru_5.5.0_3.0_1727385535882.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_russian","ru") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_russian", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_russian| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|109.5 MB| + +## References + +https://huggingface.co/mikhmanoff/bert_ru \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_samoan_gen1_large_defined_summarized_chuvash_2_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_samoan_gen1_large_defined_summarized_chuvash_2_en.md new file mode 100644 index 00000000000000..a5629e2ac643ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_samoan_gen1_large_defined_summarized_chuvash_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_samoan_gen1_large_defined_summarized_chuvash_2 BertForSequenceClassification from wiorz +author: John Snow Labs +name: bert_samoan_gen1_large_defined_summarized_chuvash_2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_gen1_large_defined_summarized_chuvash_2` is a English model originally trained by wiorz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_samoan_gen1_large_defined_summarized_chuvash_2_en_5.5.0_3.0_1727318972858.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_samoan_gen1_large_defined_summarized_chuvash_2_en_5.5.0_3.0_1727318972858.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_samoan_gen1_large_defined_summarized_chuvash_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_samoan_gen1_large_defined_summarized_chuvash_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_samoan_gen1_large_defined_summarized_chuvash_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/wiorz/bert_sm_gen1_large_defined_summarized_cv_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline_en.md new file mode 100644 index 00000000000000..aeb87b97e7315d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline pipeline BertForSequenceClassification from wiorz +author: John Snow Labs +name: bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline` is a English model originally trained by wiorz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline_en_5.5.0_3.0_1727318993760.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline_en_5.5.0_3.0_1727318993760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_samoan_gen1_large_defined_summarized_chuvash_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/wiorz/bert_sm_gen1_large_defined_summarized_cv_2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sentiment_classification_sayula_popoluca_oriya_neg_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sentiment_classification_sayula_popoluca_oriya_neg_en.md new file mode 100644 index 00000000000000..4492a39559e405 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sentiment_classification_sayula_popoluca_oriya_neg_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sentiment_classification_sayula_popoluca_oriya_neg BertForSequenceClassification from atharvapawar +author: John Snow Labs +name: bert_sentiment_classification_sayula_popoluca_oriya_neg +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sentiment_classification_sayula_popoluca_oriya_neg` is a English model originally trained by atharvapawar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sentiment_classification_sayula_popoluca_oriya_neg_en_5.5.0_3.0_1727387696381.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sentiment_classification_sayula_popoluca_oriya_neg_en_5.5.0_3.0_1727387696381.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_sentiment_classification_sayula_popoluca_oriya_neg","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sentiment_classification_sayula_popoluca_oriya_neg", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sentiment_classification_sayula_popoluca_oriya_neg| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/atharvapawar/Bert-Sentiment-Classification-pos-or-neg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline_en.md new file mode 100644 index 00000000000000..2dbbcba3151581 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline pipeline BertForSequenceClassification from atharvapawar +author: John Snow Labs +name: bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline` is a English model originally trained by atharvapawar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline_en_5.5.0_3.0_1727387719014.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline_en_5.5.0_3.0_1727387719014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sentiment_classification_sayula_popoluca_oriya_neg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/atharvapawar/Bert-Sentiment-Classification-pos-or-neg + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sequence_classifier_multilingual_sentiment_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sequence_classifier_multilingual_sentiment_pipeline_xx.md new file mode 100644 index 00000000000000..90346fb3421074 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sequence_classifier_multilingual_sentiment_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_sequence_classifier_multilingual_sentiment_pipeline pipeline BertForSequenceClassification from nlptown +author: John Snow Labs +name: bert_sequence_classifier_multilingual_sentiment_pipeline +date: 2024-09-26 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_multilingual_sentiment_pipeline` is a Multilingual model originally trained by nlptown. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_multilingual_sentiment_pipeline_xx_5.5.0_3.0_1727388551715.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_multilingual_sentiment_pipeline_xx_5.5.0_3.0_1727388551715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sequence_classifier_multilingual_sentiment_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sequence_classifier_multilingual_sentiment_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_multilingual_sentiment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding10model_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding10model_en.md new file mode 100644 index 00000000000000..7de529ad6d976b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding10model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sst2_padding10model BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst2_padding10model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst2_padding10model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst2_padding10model_en_5.5.0_3.0_1727316374741.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst2_padding10model_en_5.5.0_3.0_1727316374741.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_sst2_padding10model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sst2_padding10model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst2_padding10model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst2_padding10model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding20model_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding20model_en.md new file mode 100644 index 00000000000000..5e9b5b3d1cfc3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding20model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sst2_padding20model BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst2_padding20model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst2_padding20model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst2_padding20model_en_5.5.0_3.0_1727383434746.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst2_padding20model_en_5.5.0_3.0_1727383434746.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_sst2_padding20model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sst2_padding20model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst2_padding20model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst2_padding20model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding80model_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding80model_en.md new file mode 100644 index 00000000000000..79df5f37c9abd3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding80model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sst2_padding80model BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst2_padding80model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst2_padding80model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst2_padding80model_en_5.5.0_3.0_1727381211378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst2_padding80model_en_5.5.0_3.0_1727381211378.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_sst2_padding80model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sst2_padding80model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst2_padding80model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst2_padding80model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding80model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding80model_pipeline_en.md new file mode 100644 index 00000000000000..919318a9bf48ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst2_padding80model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sst2_padding80model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst2_padding80model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst2_padding80model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst2_padding80model_pipeline_en_5.5.0_3.0_1727381233642.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst2_padding80model_pipeline_en_5.5.0_3.0_1727381233642.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sst2_padding80model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sst2_padding80model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst2_padding80model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst2_padding80model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding0model_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding0model_en.md new file mode 100644 index 00000000000000..66b13b2b4c06ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding0model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sst5_padding0model BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst5_padding0model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst5_padding0model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst5_padding0model_en_5.5.0_3.0_1727386477352.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst5_padding0model_en_5.5.0_3.0_1727386477352.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_sst5_padding0model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sst5_padding0model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst5_padding0model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst5_padding0model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding0model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding0model_pipeline_en.md new file mode 100644 index 00000000000000..13e8a1e521f161 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding0model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sst5_padding0model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst5_padding0model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst5_padding0model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst5_padding0model_pipeline_en_5.5.0_3.0_1727386513900.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst5_padding0model_pipeline_en_5.5.0_3.0_1727386513900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sst5_padding0model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sst5_padding0model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst5_padding0model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst5_padding0model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding10model_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding10model_en.md new file mode 100644 index 00000000000000..c9fbf484b9a408 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding10model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sst5_padding10model BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst5_padding10model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst5_padding10model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst5_padding10model_en_5.5.0_3.0_1727371440207.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst5_padding10model_en_5.5.0_3.0_1727371440207.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_sst5_padding10model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sst5_padding10model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst5_padding10model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst5_padding10model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding10model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding10model_pipeline_en.md new file mode 100644 index 00000000000000..2fe451e92230c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding10model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sst5_padding10model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst5_padding10model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst5_padding10model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst5_padding10model_pipeline_en_5.5.0_3.0_1727371461979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst5_padding10model_pipeline_en_5.5.0_3.0_1727371461979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sst5_padding10model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sst5_padding10model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst5_padding10model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst5_padding10model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding40model_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding40model_en.md new file mode 100644 index 00000000000000..79b9e554e81f8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding40model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sst5_padding40model BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst5_padding40model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst5_padding40model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst5_padding40model_en_5.5.0_3.0_1727373987240.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst5_padding40model_en_5.5.0_3.0_1727373987240.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_sst5_padding40model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sst5_padding40model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst5_padding40model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst5_padding40model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding40model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding40model_pipeline_en.md new file mode 100644 index 00000000000000..7c09ea28d28486 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_sst5_padding40model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sst5_padding40model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst5_padding40model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst5_padding40model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst5_padding40model_pipeline_en_5.5.0_3.0_1727374008512.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst5_padding40model_pipeline_en_5.5.0_3.0_1727374008512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sst5_padding40model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sst5_padding40model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst5_padding40model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst5_padding40model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_suicide_detection_hk_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_suicide_detection_hk_large_pipeline_en.md new file mode 100644 index 00000000000000..cf2cc3d40b6bc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_suicide_detection_hk_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_suicide_detection_hk_large_pipeline pipeline BertForSequenceClassification from wcyat +author: John Snow Labs +name: bert_suicide_detection_hk_large_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_suicide_detection_hk_large_pipeline` is a English model originally trained by wcyat. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_suicide_detection_hk_large_pipeline_en_5.5.0_3.0_1727313543678.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_suicide_detection_hk_large_pipeline_en_5.5.0_3.0_1727313543678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_suicide_detection_hk_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_suicide_detection_hk_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_suicide_detection_hk_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|384.7 MB| + +## References + +https://huggingface.co/wcyat/bert-suicide-detection-hk-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_tiny_sst2_kd_distilbert_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_tiny_sst2_kd_distilbert_en.md new file mode 100644 index 00000000000000..50b0b588f6ae0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_tiny_sst2_kd_distilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_tiny_sst2_kd_distilbert BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_tiny_sst2_kd_distilbert +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sst2_kd_distilbert` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_sst2_kd_distilbert_en_5.5.0_3.0_1727382875955.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_sst2_kd_distilbert_en_5.5.0_3.0_1727382875955.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_tiny_sst2_kd_distilbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_sst2_kd_distilbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_sst2_kd_distilbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/gokuls/bert-tiny-sst2-KD-distilBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_tiny_sst2_kd_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_tiny_sst2_kd_distilbert_pipeline_en.md new file mode 100644 index 00000000000000..785de0438b5fde --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_tiny_sst2_kd_distilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_tiny_sst2_kd_distilbert_pipeline pipeline BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_tiny_sst2_kd_distilbert_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_sst2_kd_distilbert_pipeline` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_sst2_kd_distilbert_pipeline_en_5.5.0_3.0_1727382877204.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_sst2_kd_distilbert_pipeline_en_5.5.0_3.0_1727382877204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_tiny_sst2_kd_distilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_tiny_sst2_kd_distilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_sst2_kd_distilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|16.8 MB| + +## References + +https://huggingface.co/gokuls/bert-tiny-sst2-KD-distilBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding100model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding100model_pipeline_en.md new file mode 100644 index 00000000000000..dc733c01ac21b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding100model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_twitterfin_padding100model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_twitterfin_padding100model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitterfin_padding100model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding100model_pipeline_en_5.5.0_3.0_1727387965335.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding100model_pipeline_en_5.5.0_3.0_1727387965335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_twitterfin_padding100model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_twitterfin_padding100model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitterfin_padding100model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_twitterfin_padding100model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding30model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding30model_pipeline_en.md new file mode 100644 index 00000000000000..ff70578166a289 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding30model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_twitterfin_padding30model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_twitterfin_padding30model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitterfin_padding30model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding30model_pipeline_en_5.5.0_3.0_1727386889558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding30model_pipeline_en_5.5.0_3.0_1727386889558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_twitterfin_padding30model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_twitterfin_padding30model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitterfin_padding30model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_twitterfin_padding30model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding40model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding40model_pipeline_en.md new file mode 100644 index 00000000000000..54d4b7a2990a75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding40model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_twitterfin_padding40model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_twitterfin_padding40model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitterfin_padding40model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding40model_pipeline_en_5.5.0_3.0_1727320338120.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding40model_pipeline_en_5.5.0_3.0_1727320338120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_twitterfin_padding40model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_twitterfin_padding40model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitterfin_padding40model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_twitterfin_padding40model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding50model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding50model_pipeline_en.md new file mode 100644 index 00000000000000..9db2ce7ebcbb84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding50model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_twitterfin_padding50model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_twitterfin_padding50model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitterfin_padding50model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding50model_pipeline_en_5.5.0_3.0_1727346774052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding50model_pipeline_en_5.5.0_3.0_1727346774052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_twitterfin_padding50model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_twitterfin_padding50model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitterfin_padding50model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_twitterfin_padding50model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding60model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding60model_pipeline_en.md new file mode 100644 index 00000000000000..252233bb4e552e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bert_twitterfin_padding60model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_twitterfin_padding60model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_twitterfin_padding60model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitterfin_padding60model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding60model_pipeline_en_5.5.0_3.0_1727374844209.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding60model_pipeline_en_5.5.0_3.0_1727374844209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_twitterfin_padding60model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_twitterfin_padding60model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitterfin_padding60model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_twitterfin_padding60model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bertbase_uncased_2_actual_en.md b/docs/_posts/ahmedlone127/2024-09-26-bertbase_uncased_2_actual_en.md new file mode 100644 index 00000000000000..2cbc09075dd255 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bertbase_uncased_2_actual_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bertbase_uncased_2_actual BertForSequenceClassification from Muffins987 +author: John Snow Labs +name: bertbase_uncased_2_actual +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertbase_uncased_2_actual` is a English model originally trained by Muffins987. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertbase_uncased_2_actual_en_5.5.0_3.0_1727342943114.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertbase_uncased_2_actual_en_5.5.0_3.0_1727342943114.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("bertbase_uncased_2_actual","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertbase_uncased_2_actual", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertbase_uncased_2_actual| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Muffins987/bertbase-uncased-2-actual \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bertbase_uncased_2_actual_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bertbase_uncased_2_actual_pipeline_en.md new file mode 100644 index 00000000000000..c608e93263c0b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bertbase_uncased_2_actual_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bertbase_uncased_2_actual_pipeline pipeline BertForSequenceClassification from Muffins987 +author: John Snow Labs +name: bertbase_uncased_2_actual_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertbase_uncased_2_actual_pipeline` is a English model originally trained by Muffins987. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertbase_uncased_2_actual_pipeline_en_5.5.0_3.0_1727342965570.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertbase_uncased_2_actual_pipeline_en_5.5.0_3.0_1727342965570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bertbase_uncased_2_actual_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bertbase_uncased_2_actual_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertbase_uncased_2_actual_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Muffins987/bertbase-uncased-2-actual + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier100_en.md b/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier100_en.md new file mode 100644 index 00000000000000..c865be18d99771 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier100_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bertsmallclassifier100 BertForSequenceClassification from meetplace1 +author: John Snow Labs +name: bertsmallclassifier100 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertsmallclassifier100` is a English model originally trained by meetplace1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertsmallclassifier100_en_5.5.0_3.0_1727381666414.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertsmallclassifier100_en_5.5.0_3.0_1727381666414.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("bertsmallclassifier100","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertsmallclassifier100", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertsmallclassifier100| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/meetplace1/bertsmallclassifier100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier100_pipeline_en.md new file mode 100644 index 00000000000000..9fe6dd7993a228 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier100_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bertsmallclassifier100_pipeline pipeline BertForSequenceClassification from meetplace1 +author: John Snow Labs +name: bertsmallclassifier100_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertsmallclassifier100_pipeline` is a English model originally trained by meetplace1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertsmallclassifier100_pipeline_en_5.5.0_3.0_1727381696236.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertsmallclassifier100_pipeline_en_5.5.0_3.0_1727381696236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bertsmallclassifier100_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bertsmallclassifier100_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertsmallclassifier100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/meetplace1/bertsmallclassifier100 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier_en.md b/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier_en.md new file mode 100644 index 00000000000000..2637bab7b51e91 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bertsmallclassifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bertsmallclassifier BertForSequenceClassification from meetplace1 +author: John Snow Labs +name: bertsmallclassifier +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertsmallclassifier` is a English model originally trained by meetplace1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertsmallclassifier_en_5.5.0_3.0_1727368671982.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertsmallclassifier_en_5.5.0_3.0_1727368671982.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("bertsmallclassifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertsmallclassifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertsmallclassifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/meetplace1/bertsmallclassifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline_en.md new file mode 100644 index 00000000000000..927a7d5eeaaadb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline pipeline BertForSequenceClassification from Tech-oriented +author: John Snow Labs +name: best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline` is a English model originally trained by Tech-oriented. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline_en_5.5.0_3.0_1727373560689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline_en_5.5.0_3.0_1727373560689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_bert_uncasedbert_base_uncased_finetuned_sst2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/Tech-oriented/best_model_bert_uncasedbert-base-uncased-finetuned-sst2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_13_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_13_pipeline_en.md new file mode 100644 index 00000000000000..5a9048df4d5880 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_13_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English best_model_sst_2_32_13_pipeline pipeline BertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_sst_2_32_13_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_sst_2_32_13_pipeline` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_sst_2_32_13_pipeline_en_5.5.0_3.0_1727375261338.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_sst_2_32_13_pipeline_en_5.5.0_3.0_1727375261338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("best_model_sst_2_32_13_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("best_model_sst_2_32_13_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_sst_2_32_13_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/best_model-sst-2-32-13 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_21_en.md b/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_21_en.md new file mode 100644 index 00000000000000..fbea285a0edda3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_21_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English best_model_sst_2_32_21 BertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_sst_2_32_21 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_sst_2_32_21` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_sst_2_32_21_en_5.5.0_3.0_1727376793921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_sst_2_32_21_en_5.5.0_3.0_1727376793921.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("best_model_sst_2_32_21","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("best_model_sst_2_32_21", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_sst_2_32_21| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/best_model-sst-2-32-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_21_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_21_pipeline_en.md new file mode 100644 index 00000000000000..78526d006bffb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-best_model_sst_2_32_21_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English best_model_sst_2_32_21_pipeline pipeline BertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_sst_2_32_21_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_sst_2_32_21_pipeline` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_sst_2_32_21_pipeline_en_5.5.0_3.0_1727376815811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_sst_2_32_21_pipeline_en_5.5.0_3.0_1727376815811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("best_model_sst_2_32_21_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("best_model_sst_2_32_21_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_sst_2_32_21_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/best_model-sst-2-32-21 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bijaka_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bijaka_base_pipeline_en.md new file mode 100644 index 00000000000000..6a420446fe6585 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bijaka_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bijaka_base_pipeline pipeline BertForSequenceClassification from sidaus +author: John Snow Labs +name: bijaka_base_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bijaka_base_pipeline` is a English model originally trained by sidaus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bijaka_base_pipeline_en_5.5.0_3.0_1727352273740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bijaka_base_pipeline_en_5.5.0_3.0_1727352273740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bijaka_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bijaka_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bijaka_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.4 MB| + +## References + +https://huggingface.co/sidaus/bijaka-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bio_clinicalbert_finetuned_20pc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bio_clinicalbert_finetuned_20pc_pipeline_en.md new file mode 100644 index 00000000000000..569df007ee5aa3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bio_clinicalbert_finetuned_20pc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bio_clinicalbert_finetuned_20pc_pipeline pipeline BertForSequenceClassification from okho0653 +author: John Snow Labs +name: bio_clinicalbert_finetuned_20pc_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bio_clinicalbert_finetuned_20pc_pipeline` is a English model originally trained by okho0653. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_finetuned_20pc_pipeline_en_5.5.0_3.0_1727369394252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_finetuned_20pc_pipeline_en_5.5.0_3.0_1727369394252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bio_clinicalbert_finetuned_20pc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bio_clinicalbert_finetuned_20pc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bio_clinicalbert_finetuned_20pc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.6 MB| + +## References + +https://huggingface.co/okho0653/Bio_ClinicalBERT-finetuned-20pc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-biobert_re_trained_en.md b/docs/_posts/ahmedlone127/2024-09-26-biobert_re_trained_en.md new file mode 100644 index 00000000000000..f3a7d03f1e8425 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-biobert_re_trained_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English biobert_re_trained BertForSequenceClassification from ChrisUPM +author: John Snow Labs +name: biobert_re_trained +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_re_trained` is a English model originally trained by ChrisUPM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_re_trained_en_5.5.0_3.0_1727390617600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_re_trained_en_5.5.0_3.0_1727390617600.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("biobert_re_trained","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("biobert_re_trained", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobert_re_trained| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.3 MB| + +## References + +https://huggingface.co/ChrisUPM/BioBERT_Re_trained \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bioclinical_bert_finetuned_mtsamples_en.md b/docs/_posts/ahmedlone127/2024-09-26-bioclinical_bert_finetuned_mtsamples_en.md new file mode 100644 index 00000000000000..1e5bbbb949603b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bioclinical_bert_finetuned_mtsamples_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bioclinical_bert_finetuned_mtsamples BertForSequenceClassification from mnaylor +author: John Snow Labs +name: bioclinical_bert_finetuned_mtsamples +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_finetuned_mtsamples` is a English model originally trained by mnaylor. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bioclinical_bert_finetuned_mtsamples_en_5.5.0_3.0_1727385127930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bioclinical_bert_finetuned_mtsamples_en_5.5.0_3.0_1727385127930.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("bioclinical_bert_finetuned_mtsamples","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bioclinical_bert_finetuned_mtsamples", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bioclinical_bert_finetuned_mtsamples| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.5 MB| + +## References + +https://huggingface.co/mnaylor/bioclinical-bert-finetuned-mtsamples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-bioclinical_bert_finetuned_mtsamples_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-bioclinical_bert_finetuned_mtsamples_pipeline_en.md new file mode 100644 index 00000000000000..64b9ab0a9895fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-bioclinical_bert_finetuned_mtsamples_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bioclinical_bert_finetuned_mtsamples_pipeline pipeline BertForSequenceClassification from mnaylor +author: John Snow Labs +name: bioclinical_bert_finetuned_mtsamples_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bioclinical_bert_finetuned_mtsamples_pipeline` is a English model originally trained by mnaylor. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bioclinical_bert_finetuned_mtsamples_pipeline_en_5.5.0_3.0_1727385151085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bioclinical_bert_finetuned_mtsamples_pipeline_en_5.5.0_3.0_1727385151085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bioclinical_bert_finetuned_mtsamples_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bioclinical_bert_finetuned_mtsamples_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bioclinical_bert_finetuned_mtsamples_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.6 MB| + +## References + +https://huggingface.co/mnaylor/bioclinical-bert-finetuned-mtsamples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-boss_sentiment_6000_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-boss_sentiment_6000_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..61d48e10bf4eae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-boss_sentiment_6000_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English boss_sentiment_6000_bert_base_uncased_pipeline pipeline BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: boss_sentiment_6000_bert_base_uncased_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`boss_sentiment_6000_bert_base_uncased_pipeline` is a English model originally trained by Kyle1668. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/boss_sentiment_6000_bert_base_uncased_pipeline_en_5.5.0_3.0_1727361085113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boss_sentiment_6000_bert_base_uncased_pipeline_en_5.5.0_3.0_1727361085113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("boss_sentiment_6000_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("boss_sentiment_6000_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|boss_sentiment_6000_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/boss-sentiment-6000-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-boss_toxicity_6000_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-26-boss_toxicity_6000_bert_base_uncased_en.md new file mode 100644 index 00000000000000..8b621e52775787 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-boss_toxicity_6000_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English boss_toxicity_6000_bert_base_uncased BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: boss_toxicity_6000_bert_base_uncased +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_6000_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_6000_bert_base_uncased_en_5.5.0_3.0_1727370801809.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boss_toxicity_6000_bert_base_uncased_en_5.5.0_3.0_1727370801809.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("boss_toxicity_6000_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("boss_toxicity_6000_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|boss_toxicity_6000_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/boss-toxicity-6000-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-burmese_awesome_model_jonathanparaschou_en.md b/docs/_posts/ahmedlone127/2024-09-26-burmese_awesome_model_jonathanparaschou_en.md new file mode 100644 index 00000000000000..a79b338b750cbf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-burmese_awesome_model_jonathanparaschou_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_awesome_model_jonathanparaschou BertForSequenceClassification from jonathanparaschou +author: John Snow Labs +name: burmese_awesome_model_jonathanparaschou +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_awesome_model_jonathanparaschou` is a English model originally trained by jonathanparaschou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jonathanparaschou_en_5.5.0_3.0_1727371169281.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_model_jonathanparaschou_en_5.5.0_3.0_1727371169281.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("burmese_awesome_model_jonathanparaschou","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("burmese_awesome_model_jonathanparaschou", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_model_jonathanparaschou| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jonathanparaschou/my_awesome_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-burmese_bert_fine_tuned_psh3_en.md b/docs/_posts/ahmedlone127/2024-09-26-burmese_bert_fine_tuned_psh3_en.md new file mode 100644 index 00000000000000..521e26e9fa2ad7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-burmese_bert_fine_tuned_psh3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_bert_fine_tuned_psh3 BertForSequenceClassification from Seonghwan +author: John Snow Labs +name: burmese_bert_fine_tuned_psh3 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_fine_tuned_psh3` is a English model originally trained by Seonghwan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_bert_fine_tuned_psh3_en_5.5.0_3.0_1727343532712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_bert_fine_tuned_psh3_en_5.5.0_3.0_1727343532712.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("burmese_bert_fine_tuned_psh3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("burmese_bert_fine_tuned_psh3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_bert_fine_tuned_psh3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/Seonghwan/my-bert-fine-tuned-psh3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_chunwoolee0_en.md b/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_chunwoolee0_en.md new file mode 100644 index 00000000000000..e09e51cc07ec58 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_chunwoolee0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_doccls_korean_model_chunwoolee0 BertForSequenceClassification from chunwoolee0 +author: John Snow Labs +name: burmese_doccls_korean_model_chunwoolee0 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_doccls_korean_model_chunwoolee0` is a English model originally trained by chunwoolee0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_doccls_korean_model_chunwoolee0_en_5.5.0_3.0_1727382917721.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_doccls_korean_model_chunwoolee0_en_5.5.0_3.0_1727382917721.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("burmese_doccls_korean_model_chunwoolee0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("burmese_doccls_korean_model_chunwoolee0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_doccls_korean_model_chunwoolee0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.4 MB| + +## References + +https://huggingface.co/chunwoolee0/my_doccls_korean_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_chunwoolee0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_chunwoolee0_pipeline_en.md new file mode 100644 index 00000000000000..760a59f97275b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_chunwoolee0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_doccls_korean_model_chunwoolee0_pipeline pipeline BertForSequenceClassification from chunwoolee0 +author: John Snow Labs +name: burmese_doccls_korean_model_chunwoolee0_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_doccls_korean_model_chunwoolee0_pipeline` is a English model originally trained by chunwoolee0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_doccls_korean_model_chunwoolee0_pipeline_en_5.5.0_3.0_1727382939857.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_doccls_korean_model_chunwoolee0_pipeline_en_5.5.0_3.0_1727382939857.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_doccls_korean_model_chunwoolee0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_doccls_korean_model_chunwoolee0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_doccls_korean_model_chunwoolee0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.5 MB| + +## References + +https://huggingface.co/chunwoolee0/my_doccls_korean_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_dudu1021_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_dudu1021_pipeline_en.md new file mode 100644 index 00000000000000..1bb80f9c369fd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-burmese_doccls_korean_model_dudu1021_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_doccls_korean_model_dudu1021_pipeline pipeline BertForSequenceClassification from dudu1021 +author: John Snow Labs +name: burmese_doccls_korean_model_dudu1021_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_doccls_korean_model_dudu1021_pipeline` is a English model originally trained by dudu1021. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_doccls_korean_model_dudu1021_pipeline_en_5.5.0_3.0_1727350750622.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_doccls_korean_model_dudu1021_pipeline_en_5.5.0_3.0_1727350750622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_doccls_korean_model_dudu1021_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_doccls_korean_model_dudu1021_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_doccls_korean_model_dudu1021_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.5 MB| + +## References + +https://huggingface.co/dudu1021/my_doccls_korean_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-chinese_roberta_climate_related_prediction_v3_en.md b/docs/_posts/ahmedlone127/2024-09-26-chinese_roberta_climate_related_prediction_v3_en.md new file mode 100644 index 00000000000000..0e30b88ec6dd70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-chinese_roberta_climate_related_prediction_v3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English chinese_roberta_climate_related_prediction_v3 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: chinese_roberta_climate_related_prediction_v3 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_climate_related_prediction_v3` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_related_prediction_v3_en_5.5.0_3.0_1727389954046.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_related_prediction_v3_en_5.5.0_3.0_1727389954046.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("chinese_roberta_climate_related_prediction_v3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("chinese_roberta_climate_related_prediction_v3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_climate_related_prediction_v3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.2 MB| + +## References + +https://huggingface.co/hw2942/chinese-roberta-climate-related-prediction-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cn_bert_sci_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-cn_bert_sci_pipeline_en.md new file mode 100644 index 00000000000000..dc4b9d6a538550 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cn_bert_sci_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cn_bert_sci_pipeline pipeline BertForSequenceClassification from vishwa27 +author: John Snow Labs +name: cn_bert_sci_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cn_bert_sci_pipeline` is a English model originally trained by vishwa27. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cn_bert_sci_pipeline_en_5.5.0_3.0_1727310801448.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cn_bert_sci_pipeline_en_5.5.0_3.0_1727310801448.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cn_bert_sci_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cn_bert_sci_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cn_bert_sci_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/vishwa27/CN_BERT_Sci + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr10_seed0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr10_seed0_pipeline_en.md new file mode 100644 index 00000000000000..651bfdca8cd68d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr10_seed0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr10_seed0_pipeline pipeline BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr10_seed0_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr10_seed0_pipeline` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr10_seed0_pipeline_en_5.5.0_3.0_1727381149988.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr10_seed0_pipeline_en_5.5.0_3.0_1727381149988.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cold_fusion_bert_base_uncased_itr10_seed0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cold_fusion_bert_base_uncased_itr10_seed0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr10_seed0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr10-seed0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr16_seed0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr16_seed0_pipeline_en.md new file mode 100644 index 00000000000000..8546a16f7864f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr16_seed0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr16_seed0_pipeline pipeline BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr16_seed0_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr16_seed0_pipeline` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr16_seed0_pipeline_en_5.5.0_3.0_1727384901652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr16_seed0_pipeline_en_5.5.0_3.0_1727384901652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cold_fusion_bert_base_uncased_itr16_seed0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cold_fusion_bert_base_uncased_itr16_seed0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr16_seed0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr16-seed0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr17_seed0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr17_seed0_pipeline_en.md new file mode 100644 index 00000000000000..1aff83517d7fa4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr17_seed0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr17_seed0_pipeline pipeline BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr17_seed0_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr17_seed0_pipeline` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr17_seed0_pipeline_en_5.5.0_3.0_1727383977589.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr17_seed0_pipeline_en_5.5.0_3.0_1727383977589.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cold_fusion_bert_base_uncased_itr17_seed0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cold_fusion_bert_base_uncased_itr17_seed0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr17_seed0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr17-seed0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv_en.md b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv_en.md new file mode 100644 index 00000000000000..5978eaf026203e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv BertForSequenceClassification from jakub014 +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv_en_5.5.0_3.0_1727385065378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv_en_5.5.0_3.0_1727385065378.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("cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr23_seed0_finetuned_effectiveness_redditcmv| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/ColD-Fusion-bert-base-uncased-itr23-seed0-finetuned-effectiveness-redditCMV \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr7_seed0_en.md b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr7_seed0_en.md new file mode 100644 index 00000000000000..63346a89815aeb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr7_seed0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr7_seed0 BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr7_seed0 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr7_seed0` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr7_seed0_en_5.5.0_3.0_1727383422513.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr7_seed0_en_5.5.0_3.0_1727383422513.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("cold_fusion_bert_base_uncased_itr7_seed0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cold_fusion_bert_base_uncased_itr7_seed0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr7_seed0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr7-seed0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr8_seed0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr8_seed0_pipeline_en.md new file mode 100644 index 00000000000000..0b065bbbdc913f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cold_fusion_bert_base_uncased_itr8_seed0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr8_seed0_pipeline pipeline BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr8_seed0_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr8_seed0_pipeline` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr8_seed0_pipeline_en_5.5.0_3.0_1727344535829.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr8_seed0_pipeline_en_5.5.0_3.0_1727344535829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cold_fusion_bert_base_uncased_itr8_seed0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cold_fusion_bert_base_uncased_itr8_seed0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr8_seed0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr8-seed0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-comment_bert_purpose_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-comment_bert_purpose_pipeline_en.md new file mode 100644 index 00000000000000..da2aed6fd5ec57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-comment_bert_purpose_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English comment_bert_purpose_pipeline pipeline BertForSequenceClassification from mochodek +author: John Snow Labs +name: comment_bert_purpose_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comment_bert_purpose_pipeline` is a English model originally trained by mochodek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comment_bert_purpose_pipeline_en_5.5.0_3.0_1727383306179.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comment_bert_purpose_pipeline_en_5.5.0_3.0_1727383306179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("comment_bert_purpose_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("comment_bert_purpose_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|comment_bert_purpose_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mochodek/comment-bert-purpose + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-conv_bert_medium_small_mbib_2048_en.md b/docs/_posts/ahmedlone127/2024-09-26-conv_bert_medium_small_mbib_2048_en.md new file mode 100644 index 00000000000000..99070de6530c30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-conv_bert_medium_small_mbib_2048_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English conv_bert_medium_small_mbib_2048 BertForSequenceClassification from ANGKJ1995 +author: John Snow Labs +name: conv_bert_medium_small_mbib_2048 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conv_bert_medium_small_mbib_2048` is a English model originally trained by ANGKJ1995. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conv_bert_medium_small_mbib_2048_en_5.5.0_3.0_1727388171740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conv_bert_medium_small_mbib_2048_en_5.5.0_3.0_1727388171740.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("conv_bert_medium_small_mbib_2048","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("conv_bert_medium_small_mbib_2048", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|conv_bert_medium_small_mbib_2048| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|66.5 MB| + +## References + +https://huggingface.co/ANGKJ1995/conv-bert-medium-small-mbib-2048 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-conv_bert_medium_small_mbib_2048_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-conv_bert_medium_small_mbib_2048_pipeline_en.md new file mode 100644 index 00000000000000..04a3d5634cd57e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-conv_bert_medium_small_mbib_2048_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English conv_bert_medium_small_mbib_2048_pipeline pipeline BertForSequenceClassification from ANGKJ1995 +author: John Snow Labs +name: conv_bert_medium_small_mbib_2048_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`conv_bert_medium_small_mbib_2048_pipeline` is a English model originally trained by ANGKJ1995. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/conv_bert_medium_small_mbib_2048_pipeline_en_5.5.0_3.0_1727388180844.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/conv_bert_medium_small_mbib_2048_pipeline_en_5.5.0_3.0_1727388180844.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("conv_bert_medium_small_mbib_2048_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("conv_bert_medium_small_mbib_2048_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|conv_bert_medium_small_mbib_2048_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|66.5 MB| + +## References + +https://huggingface.co/ANGKJ1995/conv-bert-medium-small-mbib-2048 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-covid_augment_tweet_bert_large_e4_en.md b/docs/_posts/ahmedlone127/2024-09-26-covid_augment_tweet_bert_large_e4_en.md new file mode 100644 index 00000000000000..e2871d7a4bfac7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-covid_augment_tweet_bert_large_e4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English covid_augment_tweet_bert_large_e4 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_augment_tweet_bert_large_e4 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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` 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_en_5.5.0_3.0_1727380516613.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_en_5.5.0_3.0_1727380516613.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("covid_augment_tweet_bert_large_e4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_augment_tweet_bert_large_e4| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-augment-tweet-bert-large-e4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_bert_base_stsb_pipeline_it.md b/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_bert_base_stsb_pipeline_it.md new file mode 100644 index 00000000000000..8bcdedf5c293d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_bert_base_stsb_pipeline_it.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Italian cross_encoder_bert_base_stsb_pipeline pipeline BertForSequenceClassification from efederici +author: John Snow Labs +name: cross_encoder_bert_base_stsb_pipeline +date: 2024-09-26 +tags: [it, open_source, pipeline, onnx] +task: Text Classification +language: it +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_encoder_bert_base_stsb_pipeline` is a Italian model originally trained by efederici. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_encoder_bert_base_stsb_pipeline_it_5.5.0_3.0_1727343000979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_encoder_bert_base_stsb_pipeline_it_5.5.0_3.0_1727343000979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cross_encoder_bert_base_stsb_pipeline", lang = "it") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cross_encoder_bert_base_stsb_pipeline", lang = "it") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cross_encoder_bert_base_stsb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|it| +|Size:|414.8 MB| + +## References + +https://huggingface.co/efederici/cross-encoder-bert-base-stsb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_malay_marco_minilm_l_6_v2_en.md b/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_malay_marco_minilm_l_6_v2_en.md new file mode 100644 index 00000000000000..eb3db748202154 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_malay_marco_minilm_l_6_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cross_encoder_malay_marco_minilm_l_6_v2 BertForSequenceClassification from n2vec +author: John Snow Labs +name: cross_encoder_malay_marco_minilm_l_6_v2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_encoder_malay_marco_minilm_l_6_v2` is a English model originally trained by n2vec. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_encoder_malay_marco_minilm_l_6_v2_en_5.5.0_3.0_1727374369661.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_encoder_malay_marco_minilm_l_6_v2_en_5.5.0_3.0_1727374369661.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("cross_encoder_malay_marco_minilm_l_6_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cross_encoder_malay_marco_minilm_l_6_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cross_encoder_malay_marco_minilm_l_6_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|84.3 MB| + +## References + +https://huggingface.co/n2vec/cross-encoder_ms-marco-MiniLM-L-6-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_roberta_wwm_ext_large_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_roberta_wwm_ext_large_pipeline_zh.md new file mode 100644 index 00000000000000..c2be4bde4533da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cross_encoder_roberta_wwm_ext_large_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese cross_encoder_roberta_wwm_ext_large_pipeline pipeline BertForSequenceClassification from tuhailong +author: John Snow Labs +name: cross_encoder_roberta_wwm_ext_large_pipeline +date: 2024-09-26 +tags: [zh, open_source, pipeline, onnx] +task: Text Classification +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cross_encoder_roberta_wwm_ext_large_pipeline` is a Chinese model originally trained by tuhailong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cross_encoder_roberta_wwm_ext_large_pipeline_zh_5.5.0_3.0_1727333267504.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cross_encoder_roberta_wwm_ext_large_pipeline_zh_5.5.0_3.0_1727333267504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cross_encoder_roberta_wwm_ext_large_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cross_encoder_roberta_wwm_ext_large_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cross_encoder_roberta_wwm_ext_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|1.2 GB| + +## References + +https://huggingface.co/tuhailong/cross_encoder_roberta-wwm-ext-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-cs431_camera_coqe_csi_en.md b/docs/_posts/ahmedlone127/2024-09-26-cs431_camera_coqe_csi_en.md new file mode 100644 index 00000000000000..25a20a4bd68c42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-cs431_camera_coqe_csi_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cs431_camera_coqe_csi BertForSequenceClassification from ThuyNT03 +author: John Snow Labs +name: cs431_camera_coqe_csi +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs431_camera_coqe_csi` is a English model originally trained by ThuyNT03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs431_camera_coqe_csi_en_5.5.0_3.0_1727355183619.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs431_camera_coqe_csi_en_5.5.0_3.0_1727355183619.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("cs431_camera_coqe_csi","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cs431_camera_coqe_csi", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cs431_camera_coqe_csi| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ThuyNT03/CS431_Camera-COQE_CSI \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-darijaber_promotion_clf_dv2_v1_en.md b/docs/_posts/ahmedlone127/2024-09-26-darijaber_promotion_clf_dv2_v1_en.md new file mode 100644 index 00000000000000..0db4e5275b9f9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-darijaber_promotion_clf_dv2_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English darijaber_promotion_clf_dv2_v1 BertForSequenceClassification from eniafou +author: John Snow Labs +name: darijaber_promotion_clf_dv2_v1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`darijaber_promotion_clf_dv2_v1` is a English model originally trained by eniafou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/darijaber_promotion_clf_dv2_v1_en_5.5.0_3.0_1727388022834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/darijaber_promotion_clf_dv2_v1_en_5.5.0_3.0_1727388022834.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("darijaber_promotion_clf_dv2_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("darijaber_promotion_clf_dv2_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|darijaber_promotion_clf_dv2_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|553.7 MB| + +## References + +https://huggingface.co/eniafou/DarijaBER-promotion-clf-dv2_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_10_baseline_en.md b/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_10_baseline_en.md new file mode 100644 index 00000000000000..047e0be865afa2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_10_baseline_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dbpedia_classes_bert_base_uncased_few_10_baseline BertForSequenceClassification from TheChickenAgent +author: John Snow Labs +name: dbpedia_classes_bert_base_uncased_few_10_baseline +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbpedia_classes_bert_base_uncased_few_10_baseline` is a English model originally trained by TheChickenAgent. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbpedia_classes_bert_base_uncased_few_10_baseline_en_5.5.0_3.0_1727309501725.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbpedia_classes_bert_base_uncased_few_10_baseline_en_5.5.0_3.0_1727309501725.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("dbpedia_classes_bert_base_uncased_few_10_baseline","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dbpedia_classes_bert_base_uncased_few_10_baseline", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dbpedia_classes_bert_base_uncased_few_10_baseline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TheChickenAgent/DBPedia_Classes_BERT-base-uncased-few-10-baseline \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_50_baseline_en.md b/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_50_baseline_en.md new file mode 100644 index 00000000000000..44bf91471a4808 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_50_baseline_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dbpedia_classes_bert_base_uncased_few_50_baseline BertForSequenceClassification from TheChickenAgent +author: John Snow Labs +name: dbpedia_classes_bert_base_uncased_few_50_baseline +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbpedia_classes_bert_base_uncased_few_50_baseline` is a English model originally trained by TheChickenAgent. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbpedia_classes_bert_base_uncased_few_50_baseline_en_5.5.0_3.0_1727388147460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbpedia_classes_bert_base_uncased_few_50_baseline_en_5.5.0_3.0_1727388147460.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("dbpedia_classes_bert_base_uncased_few_50_baseline","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dbpedia_classes_bert_base_uncased_few_50_baseline", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dbpedia_classes_bert_base_uncased_few_50_baseline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TheChickenAgent/DBPedia_Classes_BERT-base-uncased-few-50-baseline \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline_en.md new file mode 100644 index 00000000000000..d3313d9f17abc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline pipeline BertForSequenceClassification from TheChickenAgent +author: John Snow Labs +name: dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline` is a English model originally trained by TheChickenAgent. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline_en_5.5.0_3.0_1727388169518.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline_en_5.5.0_3.0_1727388169518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dbpedia_classes_bert_base_uncased_few_50_baseline_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TheChickenAgent/DBPedia_Classes_BERT-base-uncased-few-50-baseline + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-decipher_the_code_explainer_en.md b/docs/_posts/ahmedlone127/2024-09-26-decipher_the_code_explainer_en.md new file mode 100644 index 00000000000000..df50f3b1a65997 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-decipher_the_code_explainer_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English decipher_the_code_explainer BertForSequenceClassification from tharun1507 +author: John Snow Labs +name: decipher_the_code_explainer +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`decipher_the_code_explainer` is a English model originally trained by tharun1507. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/decipher_the_code_explainer_en_5.5.0_3.0_1727328369357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/decipher_the_code_explainer_en_5.5.0_3.0_1727328369357.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("decipher_the_code_explainer","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("decipher_the_code_explainer", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|decipher_the_code_explainer| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/tharun1507/Decipher-the_code_explainer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-depressiondetectionarabert_en.md b/docs/_posts/ahmedlone127/2024-09-26-depressiondetectionarabert_en.md new file mode 100644 index 00000000000000..61ad55bd182df5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-depressiondetectionarabert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English depressiondetectionarabert BertForSequenceClassification from reem1997 +author: John Snow Labs +name: depressiondetectionarabert +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`depressiondetectionarabert` is a English model originally trained by reem1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/depressiondetectionarabert_en_5.5.0_3.0_1727386444629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/depressiondetectionarabert_en_5.5.0_3.0_1727386444629.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("depressiondetectionarabert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("depressiondetectionarabert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|depressiondetectionarabert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/reem1997/depressionDetectionArabert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-depressiondetectionarabert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-depressiondetectionarabert_pipeline_en.md new file mode 100644 index 00000000000000..0abfe4e2f48fe8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-depressiondetectionarabert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English depressiondetectionarabert_pipeline pipeline BertForSequenceClassification from reem1997 +author: John Snow Labs +name: depressiondetectionarabert_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`depressiondetectionarabert_pipeline` is a English model originally trained by reem1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/depressiondetectionarabert_pipeline_en_5.5.0_3.0_1727386474710.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/depressiondetectionarabert_pipeline_en_5.5.0_3.0_1727386474710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("depressiondetectionarabert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("depressiondetectionarabert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|depressiondetectionarabert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/reem1997/depressionDetectionArabert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-diagtrast_berto_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-26-diagtrast_berto_pipeline_es.md new file mode 100644 index 00000000000000..4200cfa92aba90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-diagtrast_berto_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish diagtrast_berto_pipeline pipeline BertForSequenceClassification from somosnlp-hackathon-2023 +author: John Snow Labs +name: diagtrast_berto_pipeline +date: 2024-09-26 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`diagtrast_berto_pipeline` is a Castilian, Spanish model originally trained by somosnlp-hackathon-2023. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/diagtrast_berto_pipeline_es_5.5.0_3.0_1727371233474.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/diagtrast_berto_pipeline_es_5.5.0_3.0_1727371233474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("diagtrast_berto_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("diagtrast_berto_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|diagtrast_berto_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/somosnlp-hackathon-2023/DiagTrast-Berto + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-distilbert_emotion_masallah_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-distilbert_emotion_masallah_pipeline_en.md new file mode 100644 index 00000000000000..d597d42bcd7ce5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-distilbert_emotion_masallah_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_emotion_masallah_pipeline pipeline BertForSequenceClassification from Masallah +author: John Snow Labs +name: distilbert_emotion_masallah_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_emotion_masallah_pipeline` is a English model originally trained by Masallah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_emotion_masallah_pipeline_en_5.5.0_3.0_1727378441277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_emotion_masallah_pipeline_en_5.5.0_3.0_1727378441277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_emotion_masallah_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_emotion_masallah_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_emotion_masallah_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.5 MB| + +## References + +https://huggingface.co/Masallah/distilbert-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-distilbert_portuguese_cased_finetuned_bec_classification_en.md b/docs/_posts/ahmedlone127/2024-09-26-distilbert_portuguese_cased_finetuned_bec_classification_en.md new file mode 100644 index 00000000000000..3c328641df6026 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-distilbert_portuguese_cased_finetuned_bec_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_portuguese_cased_finetuned_bec_classification BertForSequenceClassification from xc2450 +author: John Snow Labs +name: distilbert_portuguese_cased_finetuned_bec_classification +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_portuguese_cased_finetuned_bec_classification` is a English model originally trained by xc2450. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_portuguese_cased_finetuned_bec_classification_en_5.5.0_3.0_1727390365621.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_portuguese_cased_finetuned_bec_classification_en_5.5.0_3.0_1727390365621.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("distilbert_portuguese_cased_finetuned_bec_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("distilbert_portuguese_cased_finetuned_bec_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_portuguese_cased_finetuned_bec_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|252.3 MB| + +## References + +https://huggingface.co/xc2450/distilbert-portuguese-cased-finetuned-bec_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-distilbert_portuguese_cased_finetuned_bec_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-distilbert_portuguese_cased_finetuned_bec_classification_pipeline_en.md new file mode 100644 index 00000000000000..272c5020128698 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-distilbert_portuguese_cased_finetuned_bec_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_portuguese_cased_finetuned_bec_classification_pipeline pipeline BertForSequenceClassification from xc2450 +author: John Snow Labs +name: distilbert_portuguese_cased_finetuned_bec_classification_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_portuguese_cased_finetuned_bec_classification_pipeline` is a English model originally trained by xc2450. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_portuguese_cased_finetuned_bec_classification_pipeline_en_5.5.0_3.0_1727390378824.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_portuguese_cased_finetuned_bec_classification_pipeline_en_5.5.0_3.0_1727390378824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_portuguese_cased_finetuned_bec_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_portuguese_cased_finetuned_bec_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_portuguese_cased_finetuned_bec_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|252.4 MB| + +## References + +https://huggingface.co/xc2450/distilbert-portuguese-cased-finetuned-bec_classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-dummy_model_hefeng0_en.md b/docs/_posts/ahmedlone127/2024-09-26-dummy_model_hefeng0_en.md new file mode 100644 index 00000000000000..5c2485592a39b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-dummy_model_hefeng0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_hefeng0 BertForSequenceClassification from hefeng0 +author: John Snow Labs +name: dummy_model_hefeng0 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_hefeng0` is a English model originally trained by hefeng0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_hefeng0_en_5.5.0_3.0_1727381831163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_hefeng0_en_5.5.0_3.0_1727381831163.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("dummy_model_hefeng0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dummy_model_hefeng0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_hefeng0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/hefeng0/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline_en.md new file mode 100644 index 00000000000000..4223fed676fb84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline pipeline BertForSequenceClassification from nishantyadav +author: John Snow Labs +name: emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline` is a English model originally trained by nishantyadav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline_en_5.5.0_3.0_1727322172391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline_en_5.5.0_3.0_1727322172391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emb_crossenc_msmarco_teacher_3_bert_large_wwm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/nishantyadav/emb_crossenc_msmarco_teacher_3_bert_large_wwm + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline_en.md new file mode 100644 index 00000000000000..305cd1e6eadf90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline pipeline BertForSequenceClassification from harish +author: John Snow Labs +name: english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline` is a English model originally trained by harish. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline_en_5.5.0_3.0_1727346123728.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline_en_5.5.0_3.0_1727346123728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|english_astitchtask1a_bertbaseuncased_falsetrue_0_0_best_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/harish/EN-AStitchTask1A-BERTBaseUncased-FalseTrue-0-0-BEST + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-erlangshen_roberta_330m_causal_chinese_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-09-26-erlangshen_roberta_330m_causal_chinese_pipeline_zh.md new file mode 100644 index 00000000000000..8a28f1a880e864 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-erlangshen_roberta_330m_causal_chinese_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese erlangshen_roberta_330m_causal_chinese_pipeline pipeline BertForSequenceClassification from IDEA-CCNL +author: John Snow Labs +name: erlangshen_roberta_330m_causal_chinese_pipeline +date: 2024-09-26 +tags: [zh, open_source, pipeline, onnx] +task: Text Classification +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`erlangshen_roberta_330m_causal_chinese_pipeline` is a Chinese model originally trained by IDEA-CCNL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/erlangshen_roberta_330m_causal_chinese_pipeline_zh_5.5.0_3.0_1727389189161.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/erlangshen_roberta_330m_causal_chinese_pipeline_zh_5.5.0_3.0_1727389189161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("erlangshen_roberta_330m_causal_chinese_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("erlangshen_roberta_330m_causal_chinese_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|erlangshen_roberta_330m_causal_chinese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|1.2 GB| + +## References + +https://huggingface.co/IDEA-CCNL/Erlangshen-Roberta-330M-Causal-Chinese + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-erlangshen_roberta_330m_causal_chinese_zh.md b/docs/_posts/ahmedlone127/2024-09-26-erlangshen_roberta_330m_causal_chinese_zh.md new file mode 100644 index 00000000000000..3276d34163f7ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-erlangshen_roberta_330m_causal_chinese_zh.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Chinese erlangshen_roberta_330m_causal_chinese BertForSequenceClassification from IDEA-CCNL +author: John Snow Labs +name: erlangshen_roberta_330m_causal_chinese +date: 2024-09-26 +tags: [zh, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`erlangshen_roberta_330m_causal_chinese` is a Chinese model originally trained by IDEA-CCNL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/erlangshen_roberta_330m_causal_chinese_zh_5.5.0_3.0_1727389127977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/erlangshen_roberta_330m_causal_chinese_zh_5.5.0_3.0_1727389127977.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("erlangshen_roberta_330m_causal_chinese","zh") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("erlangshen_roberta_330m_causal_chinese", "zh") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|erlangshen_roberta_330m_causal_chinese| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|zh| +|Size:|1.2 GB| + +## References + +https://huggingface.co/IDEA-CCNL/Erlangshen-Roberta-330M-Causal-Chinese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-esci_malay_marco_minilm_l_12_v2_en.md b/docs/_posts/ahmedlone127/2024-09-26-esci_malay_marco_minilm_l_12_v2_en.md new file mode 100644 index 00000000000000..51f2cbbe8a9e3e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-esci_malay_marco_minilm_l_12_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English esci_malay_marco_minilm_l_12_v2 BertForSequenceClassification from lv12 +author: John Snow Labs +name: esci_malay_marco_minilm_l_12_v2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esci_malay_marco_minilm_l_12_v2` is a English model originally trained by lv12. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esci_malay_marco_minilm_l_12_v2_en_5.5.0_3.0_1727354021181.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esci_malay_marco_minilm_l_12_v2_en_5.5.0_3.0_1727354021181.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("esci_malay_marco_minilm_l_12_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("esci_malay_marco_minilm_l_12_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esci_malay_marco_minilm_l_12_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|124.5 MB| + +## References + +https://huggingface.co/lv12/esci-ms-marco-MiniLM-L-12-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-esci_malay_marco_minilm_l_12_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-esci_malay_marco_minilm_l_12_v2_pipeline_en.md new file mode 100644 index 00000000000000..c2e1029c664aec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-esci_malay_marco_minilm_l_12_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English esci_malay_marco_minilm_l_12_v2_pipeline pipeline BertForSequenceClassification from lv12 +author: John Snow Labs +name: esci_malay_marco_minilm_l_12_v2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esci_malay_marco_minilm_l_12_v2_pipeline` is a English model originally trained by lv12. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esci_malay_marco_minilm_l_12_v2_pipeline_en_5.5.0_3.0_1727354027633.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esci_malay_marco_minilm_l_12_v2_pipeline_en_5.5.0_3.0_1727354027633.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("esci_malay_marco_minilm_l_12_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("esci_malay_marco_minilm_l_12_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esci_malay_marco_minilm_l_12_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|124.5 MB| + +## References + +https://huggingface.co/lv12/esci-ms-marco-MiniLM-L-12-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-family_categorization_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-family_categorization_pipeline_en.md new file mode 100644 index 00000000000000..e2c6ab26c16597 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-family_categorization_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English family_categorization_pipeline pipeline BertForSequenceClassification from cihan-lyons +author: John Snow Labs +name: family_categorization_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`family_categorization_pipeline` is a English model originally trained by cihan-lyons. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/family_categorization_pipeline_en_5.5.0_3.0_1727374782527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/family_categorization_pipeline_en_5.5.0_3.0_1727374782527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("family_categorization_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("family_categorization_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|family_categorization_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cihan-lyons/family-categorization + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finbertselftrain_en.md b/docs/_posts/ahmedlone127/2024-09-26-finbertselftrain_en.md new file mode 100644 index 00000000000000..2ce315b4063113 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finbertselftrain_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finbertselftrain BertForSequenceClassification from cychiuak +author: John Snow Labs +name: finbertselftrain +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbertselftrain` is a English model originally trained by cychiuak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbertselftrain_en_5.5.0_3.0_1727372454247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbertselftrain_en_5.5.0_3.0_1727372454247.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("finbertselftrain","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finbertselftrain", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finbertselftrain| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/cychiuak/FinbertSelfTrain \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finbertselftrain_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-finbertselftrain_pipeline_en.md new file mode 100644 index 00000000000000..8ec4b08deae70f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finbertselftrain_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finbertselftrain_pipeline pipeline BertForSequenceClassification from cychiuak +author: John Snow Labs +name: finbertselftrain_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbertselftrain_pipeline` is a English model originally trained by cychiuak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbertselftrain_pipeline_en_5.5.0_3.0_1727372475061.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbertselftrain_pipeline_en_5.5.0_3.0_1727372475061.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finbertselftrain_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finbertselftrain_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finbertselftrain_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/cychiuak/FinbertSelfTrain + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-fine_tune_bert_stock_thai_aja_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-fine_tune_bert_stock_thai_aja_pipeline_en.md new file mode 100644 index 00000000000000..3285ac5d0ce66d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-fine_tune_bert_stock_thai_aja_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tune_bert_stock_thai_aja_pipeline pipeline BertForSequenceClassification from jab11769 +author: John Snow Labs +name: fine_tune_bert_stock_thai_aja_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_bert_stock_thai_aja_pipeline` is a English model originally trained by jab11769. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_bert_stock_thai_aja_pipeline_en_5.5.0_3.0_1727338808855.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_bert_stock_thai_aja_pipeline_en_5.5.0_3.0_1727338808855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tune_bert_stock_thai_aja_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tune_bert_stock_thai_aja_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_bert_stock_thai_aja_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/jab11769/fine-tune-bert-stock-thai-AJA + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_bert_base_uncased_fayez94_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_bert_base_uncased_fayez94_pipeline_en.md new file mode 100644 index 00000000000000..b324110ed69144 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_bert_base_uncased_fayez94_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_bert_base_uncased_fayez94_pipeline pipeline BertForSequenceClassification from fayez94 +author: John Snow Labs +name: fine_tuned_bert_base_uncased_fayez94_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_base_uncased_fayez94_pipeline` is a English model originally trained by fayez94. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_base_uncased_fayez94_pipeline_en_5.5.0_3.0_1727323687310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_base_uncased_fayez94_pipeline_en_5.5.0_3.0_1727323687310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_bert_base_uncased_fayez94_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_bert_base_uncased_fayez94_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bert_base_uncased_fayez94_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/fayez94/Fine-tuned-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline_en.md new file mode 100644 index 00000000000000..54829def2ebf30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline pipeline BertForSequenceClassification from research-dump +author: John Snow Labs +name: fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline_en_5.5.0_3.0_1727379113406.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline_en_5.5.0_3.0_1727379113406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bert_base_uncased_lr_2e_05_epochs_20_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/research-dump/Fine_tuned_bert-base-uncased_lr_2e-05_epochs_20 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_cb_bert_en.md b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_cb_bert_en.md new file mode 100644 index 00000000000000..a7c786a0f0f577 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_cb_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English fine_tuned_cb_bert BertForSequenceClassification from lenatr99 +author: John Snow Labs +name: fine_tuned_cb_bert +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_cb_bert` is a English model originally trained by lenatr99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_cb_bert_en_5.5.0_3.0_1727387153836.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_cb_bert_en_5.5.0_3.0_1727387153836.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("fine_tuned_cb_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_cb_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_cb_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/lenatr99/fine_tuned_cb_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_cb_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_cb_bert_pipeline_en.md new file mode 100644 index 00000000000000..2962e979c24246 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_cb_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_cb_bert_pipeline pipeline BertForSequenceClassification from lenatr99 +author: John Snow Labs +name: fine_tuned_cb_bert_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_cb_bert_pipeline` is a English model originally trained by lenatr99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_cb_bert_pipeline_en_5.5.0_3.0_1727387175289.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_cb_bert_pipeline_en_5.5.0_3.0_1727387175289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_cb_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_cb_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_cb_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/lenatr99/fine_tuned_cb_bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_english_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_english_bert_pipeline_en.md new file mode 100644 index 00000000000000..2eea9396994870 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-fine_tuned_english_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_english_bert_pipeline pipeline BertForSequenceClassification from ryan0218 +author: John Snow Labs +name: fine_tuned_english_bert_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_english_bert_pipeline` is a English model originally trained by ryan0218. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_english_bert_pipeline_en_5.5.0_3.0_1727372332100.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_english_bert_pipeline_en_5.5.0_3.0_1727372332100.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_english_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_english_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_english_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ryan0218/fine_tuned_english_bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_base_on_iemocap_5_en.md b/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_base_on_iemocap_5_en.md new file mode 100644 index 00000000000000..9f4a218e960bbb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_base_on_iemocap_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_bert_base_on_iemocap_5 BertForSequenceClassification from minoosh +author: John Snow Labs +name: finetuned_bert_base_on_iemocap_5 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_on_iemocap_5` is a English model originally trained by minoosh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_on_iemocap_5_en_5.5.0_3.0_1727383949323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_on_iemocap_5_en_5.5.0_3.0_1727383949323.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("finetuned_bert_base_on_iemocap_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_bert_base_on_iemocap_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_base_on_iemocap_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/minoosh/finetuned_bert-base-on-IEMOCAP_5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_base_on_iemocap_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_base_on_iemocap_5_pipeline_en.md new file mode 100644 index 00000000000000..014c55843363ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_base_on_iemocap_5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_bert_base_on_iemocap_5_pipeline pipeline BertForSequenceClassification from minoosh +author: John Snow Labs +name: finetuned_bert_base_on_iemocap_5_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_base_on_iemocap_5_pipeline` is a English model originally trained by minoosh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_on_iemocap_5_pipeline_en_5.5.0_3.0_1727383973242.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_on_iemocap_5_pipeline_en_5.5.0_3.0_1727383973242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_bert_base_on_iemocap_5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_bert_base_on_iemocap_5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_base_on_iemocap_5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/minoosh/finetuned_bert-base-on-IEMOCAP_5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_mrpc_oumeima_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_mrpc_oumeima_pipeline_en.md new file mode 100644 index 00000000000000..aa1f99fbb4f160 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finetuned_bert_mrpc_oumeima_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_bert_mrpc_oumeima_pipeline pipeline BertForSequenceClassification from oumeima +author: John Snow Labs +name: finetuned_bert_mrpc_oumeima_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_mrpc_oumeima_pipeline` is a English model originally trained by oumeima. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_mrpc_oumeima_pipeline_en_5.5.0_3.0_1727376516192.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_mrpc_oumeima_pipeline_en_5.5.0_3.0_1727376516192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_bert_mrpc_oumeima_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_bert_mrpc_oumeima_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_mrpc_oumeima_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/oumeima/finetuned-bert-mrpc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finetuned_bertmodel_sentimentanalysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-finetuned_bertmodel_sentimentanalysis_pipeline_en.md new file mode 100644 index 00000000000000..a1142d97b672e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finetuned_bertmodel_sentimentanalysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_bertmodel_sentimentanalysis_pipeline pipeline BertForSequenceClassification from Winnie-Kay +author: John Snow Labs +name: finetuned_bertmodel_sentimentanalysis_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bertmodel_sentimentanalysis_pipeline` is a English model originally trained by Winnie-Kay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bertmodel_sentimentanalysis_pipeline_en_5.5.0_3.0_1727384216732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bertmodel_sentimentanalysis_pipeline_en_5.5.0_3.0_1727384216732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_bertmodel_sentimentanalysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_bertmodel_sentimentanalysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bertmodel_sentimentanalysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Winnie-Kay/Finetuned_BertModel_SentimentAnalysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_analysis_bert_en.md b/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_analysis_bert_en.md new file mode 100644 index 00000000000000..1e6229d7135d37 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_analysis_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_analysis_bert BertForSequenceClassification from aruca +author: John Snow Labs +name: finetuning_sentiment_analysis_bert +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_analysis_bert` is a English model originally trained by aruca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_analysis_bert_en_5.5.0_3.0_1727385370571.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_analysis_bert_en_5.5.0_3.0_1727385370571.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("finetuning_sentiment_analysis_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuning_sentiment_analysis_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_analysis_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/aruca/finetuning-sentiment-analysis-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_analysis_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_analysis_bert_pipeline_en.md new file mode 100644 index 00000000000000..16dfffdcc157fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_analysis_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_sentiment_analysis_bert_pipeline pipeline BertForSequenceClassification from aruca +author: John Snow Labs +name: finetuning_sentiment_analysis_bert_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_analysis_bert_pipeline` is a English model originally trained by aruca. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_analysis_bert_pipeline_en_5.5.0_3.0_1727385393421.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_analysis_bert_pipeline_en_5.5.0_3.0_1727385393421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_sentiment_analysis_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_sentiment_analysis_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_analysis_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/aruca/finetuning-sentiment-analysis-bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_model_3000_samples_bert_small_en.md b/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_model_3000_samples_bert_small_en.md new file mode 100644 index 00000000000000..18d06f294a3c51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-finetuning_sentiment_model_3000_samples_bert_small_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_sentiment_model_3000_samples_bert_small BertForSequenceClassification from ShashwatDash +author: John Snow Labs +name: finetuning_sentiment_model_3000_samples_bert_small +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_sentiment_model_3000_samples_bert_small` is a English model originally trained by ShashwatDash. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_bert_small_en_5.5.0_3.0_1727345019103.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_sentiment_model_3000_samples_bert_small_en_5.5.0_3.0_1727345019103.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("finetuning_sentiment_model_3000_samples_bert_small","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuning_sentiment_model_3000_samples_bert_small", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_sentiment_model_3000_samples_bert_small| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|108.0 MB| + +## References + +https://huggingface.co/ShashwatDash/finetuning-sentiment-model-3000-samples-bert-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-gbert_face_mask_sentiment_de.md b/docs/_posts/ahmedlone127/2024-09-26-gbert_face_mask_sentiment_de.md new file mode 100644 index 00000000000000..756d8550fb401e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-gbert_face_mask_sentiment_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German gbert_face_mask_sentiment BertForSequenceClassification from slvnwhrl +author: John Snow Labs +name: gbert_face_mask_sentiment +date: 2024-09-26 +tags: [de, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_face_mask_sentiment` is a German model originally trained by slvnwhrl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_face_mask_sentiment_de_5.5.0_3.0_1727380667600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_face_mask_sentiment_de_5.5.0_3.0_1727380667600.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("gbert_face_mask_sentiment","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("gbert_face_mask_sentiment", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gbert_face_mask_sentiment| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|411.9 MB| + +## References + +https://huggingface.co/slvnwhrl/gbert-face-mask-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-gbert_face_mask_sentiment_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-26-gbert_face_mask_sentiment_pipeline_de.md new file mode 100644 index 00000000000000..58fdea610d317a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-gbert_face_mask_sentiment_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German gbert_face_mask_sentiment_pipeline pipeline BertForSequenceClassification from slvnwhrl +author: John Snow Labs +name: gbert_face_mask_sentiment_pipeline +date: 2024-09-26 +tags: [de, open_source, pipeline, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_face_mask_sentiment_pipeline` is a German model originally trained by slvnwhrl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_face_mask_sentiment_pipeline_de_5.5.0_3.0_1727380691189.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_face_mask_sentiment_pipeline_de_5.5.0_3.0_1727380691189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gbert_face_mask_sentiment_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gbert_face_mask_sentiment_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gbert_face_mask_sentiment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|411.9 MB| + +## References + +https://huggingface.co/slvnwhrl/gbert-face-mask-sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-gibberish_sentence_detection_model_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-26-gibberish_sentence_detection_model_turkish_pipeline_tr.md new file mode 100644 index 00000000000000..8491eecdd5e8fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-gibberish_sentence_detection_model_turkish_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish gibberish_sentence_detection_model_turkish_pipeline pipeline BertForSequenceClassification from TURKCELL +author: John Snow Labs +name: gibberish_sentence_detection_model_turkish_pipeline +date: 2024-09-26 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gibberish_sentence_detection_model_turkish_pipeline` is a Turkish model originally trained by TURKCELL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gibberish_sentence_detection_model_turkish_pipeline_tr_5.5.0_3.0_1727313150543.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gibberish_sentence_detection_model_turkish_pipeline_tr_5.5.0_3.0_1727313150543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gibberish_sentence_detection_model_turkish_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gibberish_sentence_detection_model_turkish_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gibberish_sentence_detection_model_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|691.6 MB| + +## References + +https://huggingface.co/TURKCELL/gibberish-sentence-detection-model-tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-gibberish_sentence_detection_model_turkish_tr.md b/docs/_posts/ahmedlone127/2024-09-26-gibberish_sentence_detection_model_turkish_tr.md new file mode 100644 index 00000000000000..c9c7e352b1c012 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-gibberish_sentence_detection_model_turkish_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish gibberish_sentence_detection_model_turkish BertForSequenceClassification from TURKCELL +author: John Snow Labs +name: gibberish_sentence_detection_model_turkish +date: 2024-09-26 +tags: [tr, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gibberish_sentence_detection_model_turkish` is a Turkish model originally trained by TURKCELL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gibberish_sentence_detection_model_turkish_tr_5.5.0_3.0_1727313114270.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gibberish_sentence_detection_model_turkish_tr_5.5.0_3.0_1727313114270.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("gibberish_sentence_detection_model_turkish","tr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("gibberish_sentence_detection_model_turkish", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gibberish_sentence_detection_model_turkish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|691.6 MB| + +## References + +https://huggingface.co/TURKCELL/gibberish-sentence-detection-model-tr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-goemotions_bertspanish_finetunig_d_en.md b/docs/_posts/ahmedlone127/2024-09-26-goemotions_bertspanish_finetunig_d_en.md new file mode 100644 index 00000000000000..2fd79656d463ff --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-goemotions_bertspanish_finetunig_d_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English goemotions_bertspanish_finetunig_d BertForSequenceClassification from mrovejaxd +author: John Snow Labs +name: goemotions_bertspanish_finetunig_d +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goemotions_bertspanish_finetunig_d` is a English model originally trained by mrovejaxd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goemotions_bertspanish_finetunig_d_en_5.5.0_3.0_1727382371562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goemotions_bertspanish_finetunig_d_en_5.5.0_3.0_1727382371562.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("goemotions_bertspanish_finetunig_d","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goemotions_bertspanish_finetunig_d", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goemotions_bertspanish_finetunig_d| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.8 MB| + +## References + +https://huggingface.co/mrovejaxd/goemotions_bertspanish_finetunig_d \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-google_bert_bert_base_uncased_classification_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-26-google_bert_bert_base_uncased_classification_finetuned_en.md new file mode 100644 index 00000000000000..abd3eaa7be25be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-google_bert_bert_base_uncased_classification_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English google_bert_bert_base_uncased_classification_finetuned BertForSequenceClassification from arminmehrabian +author: John Snow Labs +name: google_bert_bert_base_uncased_classification_finetuned +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_bert_bert_base_uncased_classification_finetuned` is a English model originally trained by arminmehrabian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_bert_bert_base_uncased_classification_finetuned_en_5.5.0_3.0_1727322969536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_bert_bert_base_uncased_classification_finetuned_en_5.5.0_3.0_1727322969536.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("google_bert_bert_base_uncased_classification_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("google_bert_bert_base_uncased_classification_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|google_bert_bert_base_uncased_classification_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/arminmehrabian/google-bert-bert-base-uncased-classification-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-gut_1024_finetuned_lora_bert_base_t2t_en.md b/docs/_posts/ahmedlone127/2024-09-26-gut_1024_finetuned_lora_bert_base_t2t_en.md new file mode 100644 index 00000000000000..6f31c977cd16da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-gut_1024_finetuned_lora_bert_base_t2t_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English gut_1024_finetuned_lora_bert_base_t2t BertForSequenceClassification from LiukG +author: John Snow Labs +name: gut_1024_finetuned_lora_bert_base_t2t +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gut_1024_finetuned_lora_bert_base_t2t` is a English model originally trained by LiukG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gut_1024_finetuned_lora_bert_base_t2t_en_5.5.0_3.0_1727385860702.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gut_1024_finetuned_lora_bert_base_t2t_en_5.5.0_3.0_1727385860702.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("gut_1024_finetuned_lora_bert_base_t2t","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("gut_1024_finetuned_lora_bert_base_t2t", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gut_1024_finetuned_lora_bert_base_t2t| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|322.1 MB| + +## References + +https://huggingface.co/LiukG/gut_1024-finetuned-lora-bert-base-t2t \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-gut_1024_finetuned_lora_bert_base_t2t_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-gut_1024_finetuned_lora_bert_base_t2t_pipeline_en.md new file mode 100644 index 00000000000000..bf161755b7a864 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-gut_1024_finetuned_lora_bert_base_t2t_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gut_1024_finetuned_lora_bert_base_t2t_pipeline pipeline BertForSequenceClassification from LiukG +author: John Snow Labs +name: gut_1024_finetuned_lora_bert_base_t2t_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gut_1024_finetuned_lora_bert_base_t2t_pipeline` is a English model originally trained by LiukG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gut_1024_finetuned_lora_bert_base_t2t_pipeline_en_5.5.0_3.0_1727385918659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gut_1024_finetuned_lora_bert_base_t2t_pipeline_en_5.5.0_3.0_1727385918659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gut_1024_finetuned_lora_bert_base_t2t_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gut_1024_finetuned_lora_bert_base_t2t_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gut_1024_finetuned_lora_bert_base_t2t_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|322.1 MB| + +## References + +https://huggingface.co/LiukG/gut_1024-finetuned-lora-bert-base-t2t + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-harssment_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-26-harssment_classifier_en.md new file mode 100644 index 00000000000000..9e71d727bf64fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-harssment_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English harssment_classifier BertForSequenceClassification from abdulelahagr +author: John Snow Labs +name: harssment_classifier +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`harssment_classifier` is a English model originally trained by abdulelahagr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/harssment_classifier_en_5.5.0_3.0_1727380179509.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/harssment_classifier_en_5.5.0_3.0_1727380179509.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("harssment_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("harssment_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|harssment_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/abdulelahagr/harssment_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-harssment_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-harssment_classifier_pipeline_en.md new file mode 100644 index 00000000000000..ba634e1efa4686 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-harssment_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English harssment_classifier_pipeline pipeline BertForSequenceClassification from abdulelahagr +author: John Snow Labs +name: harssment_classifier_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`harssment_classifier_pipeline` is a English model originally trained by abdulelahagr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/harssment_classifier_pipeline_en_5.5.0_3.0_1727380211896.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/harssment_classifier_pipeline_en_5.5.0_3.0_1727380211896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("harssment_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("harssment_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|harssment_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/abdulelahagr/harssment_classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-hatebert_hate_offensive_normal_speech_lr_2e_05_en.md b/docs/_posts/ahmedlone127/2024-09-26-hatebert_hate_offensive_normal_speech_lr_2e_05_en.md new file mode 100644 index 00000000000000..a6628bb4a269e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-hatebert_hate_offensive_normal_speech_lr_2e_05_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hatebert_hate_offensive_normal_speech_lr_2e_05 BertForSequenceClassification from DrishtiSharma +author: John Snow Labs +name: hatebert_hate_offensive_normal_speech_lr_2e_05 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_hate_offensive_normal_speech_lr_2e_05` is a English model originally trained by DrishtiSharma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatebert_hate_offensive_normal_speech_lr_2e_05_en_5.5.0_3.0_1727368447292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatebert_hate_offensive_normal_speech_lr_2e_05_en_5.5.0_3.0_1727368447292.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("hatebert_hate_offensive_normal_speech_lr_2e_05","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hatebert_hate_offensive_normal_speech_lr_2e_05", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hatebert_hate_offensive_normal_speech_lr_2e_05| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.4 MB| + +## References + +https://huggingface.co/DrishtiSharma/hateBERT-hate-offensive-normal-speech-lr-2e-05 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline_en.md new file mode 100644 index 00000000000000..24e8d67fb1d2fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline pipeline BertForSequenceClassification from DrishtiSharma +author: John Snow Labs +name: hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline` is a English model originally trained by DrishtiSharma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline_en_5.5.0_3.0_1727368468179.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline_en_5.5.0_3.0_1727368468179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hatebert_hate_offensive_normal_speech_lr_2e_05_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.4 MB| + +## References + +https://huggingface.co/DrishtiSharma/hateBERT-hate-offensive-normal-speech-lr-2e-05 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-hing_mbert_ours_rundi_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-hing_mbert_ours_rundi_5_pipeline_en.md new file mode 100644 index 00000000000000..5c406b641cb848 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-hing_mbert_ours_rundi_5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hing_mbert_ours_rundi_5_pipeline pipeline BertForSequenceClassification from SkyR +author: John Snow Labs +name: hing_mbert_ours_rundi_5_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hing_mbert_ours_rundi_5_pipeline` is a English model originally trained by SkyR. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hing_mbert_ours_rundi_5_pipeline_en_5.5.0_3.0_1727343554331.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hing_mbert_ours_rundi_5_pipeline_en_5.5.0_3.0_1727343554331.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hing_mbert_ours_rundi_5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hing_mbert_ours_rundi_5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hing_mbert_ours_rundi_5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|667.2 MB| + +## References + +https://huggingface.co/SkyR/hing-mbert-ours-run-5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-hiv_v3_bodysite_en.md b/docs/_posts/ahmedlone127/2024-09-26-hiv_v3_bodysite_en.md new file mode 100644 index 00000000000000..262865efabd171 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-hiv_v3_bodysite_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hiv_v3_bodysite BertForSequenceClassification from damlab +author: John Snow Labs +name: hiv_v3_bodysite +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hiv_v3_bodysite` is a English model originally trained by damlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hiv_v3_bodysite_en_5.5.0_3.0_1727379395883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hiv_v3_bodysite_en_5.5.0_3.0_1727379395883.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("hiv_v3_bodysite","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hiv_v3_bodysite", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hiv_v3_bodysite| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/damlab/HIV_V3_bodysite \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline_en.md new file mode 100644 index 00000000000000..6a7b3184d42137 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline pipeline BertForSequenceClassification from BucketOfFish +author: John Snow Labs +name: huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline` is a English model originally trained by BucketOfFish. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline_en_5.5.0_3.0_1727379295751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline_en_5.5.0_3.0_1727379295751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|huggingface_push_tonga_tonga_islands_hub_tutorial_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/BucketOfFish/huggingface_push_to_hub_tutorial + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-hyp_only_llama_chat_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-hyp_only_llama_chat_pipeline_en.md new file mode 100644 index 00000000000000..ebef5c3b706c15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-hyp_only_llama_chat_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hyp_only_llama_chat_pipeline pipeline BertForSequenceClassification from grace-pro +author: John Snow Labs +name: hyp_only_llama_chat_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hyp_only_llama_chat_pipeline` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hyp_only_llama_chat_pipeline_en_5.5.0_3.0_1727384783687.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hyp_only_llama_chat_pipeline_en_5.5.0_3.0_1727384783687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hyp_only_llama_chat_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hyp_only_llama_chat_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hyp_only_llama_chat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/hyp_only_llama_chat + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-hyp_only_machine_gen_en.md b/docs/_posts/ahmedlone127/2024-09-26-hyp_only_machine_gen_en.md new file mode 100644 index 00000000000000..c414e036a343f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-hyp_only_machine_gen_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hyp_only_machine_gen BertForSequenceClassification from grace-pro +author: John Snow Labs +name: hyp_only_machine_gen +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hyp_only_machine_gen` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hyp_only_machine_gen_en_5.5.0_3.0_1727387797097.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hyp_only_machine_gen_en_5.5.0_3.0_1727387797097.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("hyp_only_machine_gen","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hyp_only_machine_gen", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hyp_only_machine_gen| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/hyp_only_machine_gen \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-i04_pc_en.md b/docs/_posts/ahmedlone127/2024-09-26-i04_pc_en.md new file mode 100644 index 00000000000000..180a25b49e817f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-i04_pc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English i04_pc BertForSequenceClassification from Anwaarma +author: John Snow Labs +name: i04_pc +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`i04_pc` is a English model originally trained by Anwaarma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/i04_pc_en_5.5.0_3.0_1727376370637.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/i04_pc_en_5.5.0_3.0_1727376370637.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("i04_pc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("i04_pc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|i04_pc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Anwaarma/I04-PC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-i04_pc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-i04_pc_pipeline_en.md new file mode 100644 index 00000000000000..8dbe514d0746f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-i04_pc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English i04_pc_pipeline pipeline BertForSequenceClassification from Anwaarma +author: John Snow Labs +name: i04_pc_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`i04_pc_pipeline` is a English model originally trained by Anwaarma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/i04_pc_pipeline_en_5.5.0_3.0_1727376371910.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/i04_pc_pipeline_en_5.5.0_3.0_1727376371910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("i04_pc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("i04_pc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|i04_pc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|16.8 MB| + +## References + +https://huggingface.co/Anwaarma/I04-PC + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-iab_categories_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-iab_categories_classification_pipeline_en.md new file mode 100644 index 00000000000000..4a3a1670a37ec2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-iab_categories_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English iab_categories_classification_pipeline pipeline BertForSequenceClassification from PavanDeepak +author: John Snow Labs +name: iab_categories_classification_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`iab_categories_classification_pipeline` is a English model originally trained by PavanDeepak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/iab_categories_classification_pipeline_en_5.5.0_3.0_1727339454477.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/iab_categories_classification_pipeline_en_5.5.0_3.0_1727339454477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("iab_categories_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("iab_categories_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|iab_categories_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.1 MB| + +## References + +https://huggingface.co/PavanDeepak/IAB_Categories_Classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-imamu_arabic_sentimentanalysis_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-26-imamu_arabic_sentimentanalysis_pipeline_ar.md new file mode 100644 index 00000000000000..366ec5376b21d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-imamu_arabic_sentimentanalysis_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic imamu_arabic_sentimentanalysis_pipeline pipeline BertForSequenceClassification from ALANZI +author: John Snow Labs +name: imamu_arabic_sentimentanalysis_pipeline +date: 2024-09-26 +tags: [ar, open_source, pipeline, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imamu_arabic_sentimentanalysis_pipeline` is a Arabic model originally trained by ALANZI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imamu_arabic_sentimentanalysis_pipeline_ar_5.5.0_3.0_1727324892902.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imamu_arabic_sentimentanalysis_pipeline_ar_5.5.0_3.0_1727324892902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("imamu_arabic_sentimentanalysis_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("imamu_arabic_sentimentanalysis_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imamu_arabic_sentimentanalysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|408.8 MB| + +## References + +https://huggingface.co/ALANZI/imamu_arabic_sentimentAnalysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-imdb_bert_5e_en.md b/docs/_posts/ahmedlone127/2024-09-26-imdb_bert_5e_en.md new file mode 100644 index 00000000000000..26a0a0213be952 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-imdb_bert_5e_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English imdb_bert_5e BertForSequenceClassification from pig4431 +author: John Snow Labs +name: imdb_bert_5e +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_5e` is a English model originally trained by pig4431. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_bert_5e_en_5.5.0_3.0_1727352255920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_bert_5e_en_5.5.0_3.0_1727352255920.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("imdb_bert_5e","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("imdb_bert_5e", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imdb_bert_5e| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/pig4431/IMDB_BERT_5E \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-incidentimpactmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-incidentimpactmodel_pipeline_en.md new file mode 100644 index 00000000000000..3162a6e3ec3c0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-incidentimpactmodel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English incidentimpactmodel_pipeline pipeline BertForSequenceClassification from xeroISB +author: John Snow Labs +name: incidentimpactmodel_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incidentimpactmodel_pipeline` is a English model originally trained by xeroISB. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incidentimpactmodel_pipeline_en_5.5.0_3.0_1727386283848.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incidentimpactmodel_pipeline_en_5.5.0_3.0_1727386283848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("incidentimpactmodel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("incidentimpactmodel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|incidentimpactmodel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/xeroISB/incidentImpactModel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-intent_classifier_bert_base_less_eval_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-intent_classifier_bert_base_less_eval_pipeline_en.md new file mode 100644 index 00000000000000..e09fb98be22194 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-intent_classifier_bert_base_less_eval_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English intent_classifier_bert_base_less_eval_pipeline pipeline BertForSequenceClassification from mlovelli +author: John Snow Labs +name: intent_classifier_bert_base_less_eval_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`intent_classifier_bert_base_less_eval_pipeline` is a English model originally trained by mlovelli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/intent_classifier_bert_base_less_eval_pipeline_en_5.5.0_3.0_1727345146098.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/intent_classifier_bert_base_less_eval_pipeline_en_5.5.0_3.0_1727345146098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("intent_classifier_bert_base_less_eval_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("intent_classifier_bert_base_less_eval_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|intent_classifier_bert_base_less_eval_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/mlovelli/intent_classifier_bert_base_less_eval + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-junlong_huanzong_twitter_financial_news_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-26-junlong_huanzong_twitter_financial_news_sentiment_analysis_en.md new file mode 100644 index 00000000000000..8ab074fb250916 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-junlong_huanzong_twitter_financial_news_sentiment_analysis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English junlong_huanzong_twitter_financial_news_sentiment_analysis BertForSequenceClassification from Andyhahaha +author: John Snow Labs +name: junlong_huanzong_twitter_financial_news_sentiment_analysis +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`junlong_huanzong_twitter_financial_news_sentiment_analysis` is a English model originally trained by Andyhahaha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/junlong_huanzong_twitter_financial_news_sentiment_analysis_en_5.5.0_3.0_1727373417991.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/junlong_huanzong_twitter_financial_news_sentiment_analysis_en_5.5.0_3.0_1727373417991.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("junlong_huanzong_twitter_financial_news_sentiment_analysis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("junlong_huanzong_twitter_financial_news_sentiment_analysis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|junlong_huanzong_twitter_financial_news_sentiment_analysis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/Andyhahaha/Junlong-Huanzong-twitter-financial-news-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-kd_bertbase_berttiny_en.md b/docs/_posts/ahmedlone127/2024-09-26-kd_bertbase_berttiny_en.md new file mode 100644 index 00000000000000..028cf5608d90fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-kd_bertbase_berttiny_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English kd_bertbase_berttiny BertForSequenceClassification from thewiz +author: John Snow Labs +name: kd_bertbase_berttiny +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_bertbase_berttiny` is a English model originally trained by thewiz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kd_bertbase_berttiny_en_5.5.0_3.0_1727374687378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kd_bertbase_berttiny_en_5.5.0_3.0_1727374687378.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("kd_bertbase_berttiny","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("kd_bertbase_berttiny", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kd_bertbase_berttiny| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/thewiz/kd-bertBase-bertTiny \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-kd_bertbase_berttiny_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-kd_bertbase_berttiny_pipeline_en.md new file mode 100644 index 00000000000000..dfa56e5c1bdcde --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-kd_bertbase_berttiny_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English kd_bertbase_berttiny_pipeline pipeline BertForSequenceClassification from thewiz +author: John Snow Labs +name: kd_bertbase_berttiny_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kd_bertbase_berttiny_pipeline` is a English model originally trained by thewiz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kd_bertbase_berttiny_pipeline_en_5.5.0_3.0_1727374688679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kd_bertbase_berttiny_pipeline_en_5.5.0_3.0_1727374688679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("kd_bertbase_berttiny_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("kd_bertbase_berttiny_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kd_bertbase_berttiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|16.8 MB| + +## References + +https://huggingface.co/thewiz/kd-bertBase-bertTiny + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-krbert_ft_en.md b/docs/_posts/ahmedlone127/2024-09-26-krbert_ft_en.md new file mode 100644 index 00000000000000..6b16b5b522346c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-krbert_ft_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English krbert_ft BertForSequenceClassification from yeye776 +author: John Snow Labs +name: krbert_ft +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`krbert_ft` is a English model originally trained by yeye776. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/krbert_ft_en_5.5.0_3.0_1727324071204.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/krbert_ft_en_5.5.0_3.0_1727324071204.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("krbert_ft","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("krbert_ft", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|krbert_ft| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|369.5 MB| + +## References + +https://huggingface.co/yeye776/KRBERT-ft \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-language_detection_bert_base_uncased_additional_en.md b/docs/_posts/ahmedlone127/2024-09-26-language_detection_bert_base_uncased_additional_en.md new file mode 100644 index 00000000000000..59a1645b883d11 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-language_detection_bert_base_uncased_additional_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English language_detection_bert_base_uncased_additional BertForSequenceClassification from jkhan447 +author: John Snow Labs +name: language_detection_bert_base_uncased_additional +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`language_detection_bert_base_uncased_additional` is a English model originally trained by jkhan447. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/language_detection_bert_base_uncased_additional_en_5.5.0_3.0_1727386650747.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/language_detection_bert_base_uncased_additional_en_5.5.0_3.0_1727386650747.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("language_detection_bert_base_uncased_additional","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("language_detection_bert_base_uncased_additional", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|language_detection_bert_base_uncased_additional| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jkhan447/language-detection-Bert-base-uncased-additional \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-latdistilledmodel_en.md b/docs/_posts/ahmedlone127/2024-09-26-latdistilledmodel_en.md new file mode 100644 index 00000000000000..98426053b8138c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-latdistilledmodel_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English latdistilledmodel BertForSequenceClassification from privacy-tech-lab +author: John Snow Labs +name: latdistilledmodel +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latdistilledmodel` is a English model originally trained by privacy-tech-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latdistilledmodel_en_5.5.0_3.0_1727377537291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latdistilledmodel_en_5.5.0_3.0_1727377537291.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("latdistilledmodel","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("latdistilledmodel", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|latdistilledmodel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/privacy-tech-lab/LatDistilledModel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-latdistilledmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-latdistilledmodel_pipeline_en.md new file mode 100644 index 00000000000000..e5eedc964a0985 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-latdistilledmodel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English latdistilledmodel_pipeline pipeline BertForSequenceClassification from privacy-tech-lab +author: John Snow Labs +name: latdistilledmodel_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latdistilledmodel_pipeline` is a English model originally trained by privacy-tech-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latdistilledmodel_pipeline_en_5.5.0_3.0_1727377541259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latdistilledmodel_pipeline_en_5.5.0_3.0_1727377541259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("latdistilledmodel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("latdistilledmodel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|latdistilledmodel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/privacy-tech-lab/LatDistilledModel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-latmodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-latmodel_pipeline_en.md new file mode 100644 index 00000000000000..54231476bee3ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-latmodel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English latmodel_pipeline pipeline BertForSequenceClassification from privacy-tech-lab +author: John Snow Labs +name: latmodel_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`latmodel_pipeline` is a English model originally trained by privacy-tech-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/latmodel_pipeline_en_5.5.0_3.0_1727350198808.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/latmodel_pipeline_en_5.5.0_3.0_1727350198808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("latmodel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("latmodel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|latmodel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/privacy-tech-lab/LatModel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-layer_1_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-26-layer_1_classifier_en.md new file mode 100644 index 00000000000000..63c1701f287239 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-layer_1_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English layer_1_classifier BertForSequenceClassification from batman555 +author: John Snow Labs +name: layer_1_classifier +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`layer_1_classifier` is a English model originally trained by batman555. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/layer_1_classifier_en_5.5.0_3.0_1727387956342.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/layer_1_classifier_en_5.5.0_3.0_1727387956342.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("layer_1_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("layer_1_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|layer_1_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/batman555/layer_1_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-layer_1_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-layer_1_classifier_pipeline_en.md new file mode 100644 index 00000000000000..42d6a63a7e5508 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-layer_1_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English layer_1_classifier_pipeline pipeline BertForSequenceClassification from batman555 +author: John Snow Labs +name: layer_1_classifier_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`layer_1_classifier_pipeline` is a English model originally trained by batman555. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/layer_1_classifier_pipeline_en_5.5.0_3.0_1727387977864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/layer_1_classifier_pipeline_en_5.5.0_3.0_1727387977864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("layer_1_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("layer_1_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|layer_1_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/batman555/layer_1_classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-legal_bert_base_uncased_5_epochs_fine_tune_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-legal_bert_base_uncased_5_epochs_fine_tune_pipeline_en.md new file mode 100644 index 00000000000000..2627b24abd430e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-legal_bert_base_uncased_5_epochs_fine_tune_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English legal_bert_base_uncased_5_epochs_fine_tune_pipeline pipeline BertForSequenceClassification from xshubhamx +author: John Snow Labs +name: legal_bert_base_uncased_5_epochs_fine_tune_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_bert_base_uncased_5_epochs_fine_tune_pipeline` is a English model originally trained by xshubhamx. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_bert_base_uncased_5_epochs_fine_tune_pipeline_en_5.5.0_3.0_1727385293883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_bert_base_uncased_5_epochs_fine_tune_pipeline_en_5.5.0_3.0_1727385293883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legal_bert_base_uncased_5_epochs_fine_tune_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legal_bert_base_uncased_5_epochs_fine_tune_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_bert_base_uncased_5_epochs_fine_tune_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/xshubhamx/legal-bert-base-uncased-5-epochs-fine-tune + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-legal_bert_samoan_gen1_large_defined_chuvash_1_en.md b/docs/_posts/ahmedlone127/2024-09-26-legal_bert_samoan_gen1_large_defined_chuvash_1_en.md new file mode 100644 index 00000000000000..829295866c4035 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-legal_bert_samoan_gen1_large_defined_chuvash_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English legal_bert_samoan_gen1_large_defined_chuvash_1 BertForSequenceClassification from wiorz +author: John Snow Labs +name: legal_bert_samoan_gen1_large_defined_chuvash_1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_samoan_gen1_large_defined_chuvash_1` is a English model originally trained by wiorz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_bert_samoan_gen1_large_defined_chuvash_1_en_5.5.0_3.0_1727380179565.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_bert_samoan_gen1_large_defined_chuvash_1_en_5.5.0_3.0_1727380179565.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("legal_bert_samoan_gen1_large_defined_chuvash_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("legal_bert_samoan_gen1_large_defined_chuvash_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_bert_samoan_gen1_large_defined_chuvash_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/wiorz/legal_bert_sm_gen1_large_defined_cv_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-legalbert_large_1_7m_1_class_actions_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-legalbert_large_1_7m_1_class_actions_pipeline_en.md new file mode 100644 index 00000000000000..648407fc534419 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-legalbert_large_1_7m_1_class_actions_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English legalbert_large_1_7m_1_class_actions_pipeline pipeline BertForSequenceClassification from afsuarezg +author: John Snow Labs +name: legalbert_large_1_7m_1_class_actions_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legalbert_large_1_7m_1_class_actions_pipeline` is a English model originally trained by afsuarezg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legalbert_large_1_7m_1_class_actions_pipeline_en_5.5.0_3.0_1727362468012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legalbert_large_1_7m_1_class_actions_pipeline_en_5.5.0_3.0_1727362468012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legalbert_large_1_7m_1_class_actions_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legalbert_large_1_7m_1_class_actions_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legalbert_large_1_7m_1_class_actions_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/afsuarezg/legalbert-large-1.7M-1_class_actions + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-legalpro_bert_base_en.md b/docs/_posts/ahmedlone127/2024-09-26-legalpro_bert_base_en.md new file mode 100644 index 00000000000000..5a33f99d0e79b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-legalpro_bert_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English legalpro_bert_base BertForSequenceClassification from AmitTewari +author: John Snow Labs +name: legalpro_bert_base +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legalpro_bert_base` is a English model originally trained by AmitTewari. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legalpro_bert_base_en_5.5.0_3.0_1727359271091.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legalpro_bert_base_en_5.5.0_3.0_1727359271091.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("legalpro_bert_base","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("legalpro_bert_base", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legalpro_bert_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/AmitTewari/LegalPro-BERT-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-log_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-log_classifier_pipeline_en.md new file mode 100644 index 00000000000000..5c1c85eb88c222 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-log_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English log_classifier_pipeline pipeline BertForSequenceClassification from SzymonSt2808 +author: John Snow Labs +name: log_classifier_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`log_classifier_pipeline` is a English model originally trained by SzymonSt2808. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/log_classifier_pipeline_en_5.5.0_3.0_1727381265817.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/log_classifier_pipeline_en_5.5.0_3.0_1727381265817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("log_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("log_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|log_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/SzymonSt2808/log_classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-lstm_finetuning_sentiment_model_3000_samples_en.md b/docs/_posts/ahmedlone127/2024-09-26-lstm_finetuning_sentiment_model_3000_samples_en.md new file mode 100644 index 00000000000000..fdff76886d03f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-lstm_finetuning_sentiment_model_3000_samples_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lstm_finetuning_sentiment_model_3000_samples BertForSequenceClassification from LYTinn +author: John Snow Labs +name: lstm_finetuning_sentiment_model_3000_samples +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lstm_finetuning_sentiment_model_3000_samples` is a English model originally trained by LYTinn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lstm_finetuning_sentiment_model_3000_samples_en_5.5.0_3.0_1727385224210.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lstm_finetuning_sentiment_model_3000_samples_en_5.5.0_3.0_1727385224210.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("lstm_finetuning_sentiment_model_3000_samples","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("lstm_finetuning_sentiment_model_3000_samples", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lstm_finetuning_sentiment_model_3000_samples| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|43.8 MB| + +## References + +https://huggingface.co/LYTinn/lstm-finetuning-sentiment-model-3000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-lstm_finetuning_sentiment_model_3000_samples_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-lstm_finetuning_sentiment_model_3000_samples_pipeline_en.md new file mode 100644 index 00000000000000..be8b55a3ec6d17 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-lstm_finetuning_sentiment_model_3000_samples_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lstm_finetuning_sentiment_model_3000_samples_pipeline pipeline BertForSequenceClassification from LYTinn +author: John Snow Labs +name: lstm_finetuning_sentiment_model_3000_samples_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lstm_finetuning_sentiment_model_3000_samples_pipeline` is a English model originally trained by LYTinn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lstm_finetuning_sentiment_model_3000_samples_pipeline_en_5.5.0_3.0_1727385226669.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lstm_finetuning_sentiment_model_3000_samples_pipeline_en_5.5.0_3.0_1727385226669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lstm_finetuning_sentiment_model_3000_samples_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lstm_finetuning_sentiment_model_3000_samples_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lstm_finetuning_sentiment_model_3000_samples_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|43.8 MB| + +## References + +https://huggingface.co/LYTinn/lstm-finetuning-sentiment-model-3000-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-m3_deeplearning_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-m3_deeplearning_pipeline_en.md new file mode 100644 index 00000000000000..3855c991ec3055 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-m3_deeplearning_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English m3_deeplearning_pipeline pipeline BertForSequenceClassification from Thysted +author: John Snow Labs +name: m3_deeplearning_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m3_deeplearning_pipeline` is a English model originally trained by Thysted. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m3_deeplearning_pipeline_en_5.5.0_3.0_1727319375796.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m3_deeplearning_pipeline_en_5.5.0_3.0_1727319375796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("m3_deeplearning_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("m3_deeplearning_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|m3_deeplearning_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Thysted/M3-DeepLearning + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline_en.md new file mode 100644 index 00000000000000..ae2b9cd765099a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline pipeline BertForSequenceClassification from liangyuant +author: John Snow Labs +name: malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline` is a English model originally trained by liangyuant. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline_en_5.5.0_3.0_1727376458845.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline_en_5.5.0_3.0_1727376458845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|malay_marco_minilm_l_12_v2_finetuned_10epoch_num200_450_405cls_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|124.8 MB| + +## References + +https://huggingface.co/liangyuant/ms-marco-MiniLM-L-12-v2-finetuned-10epoch-num200-450-405cls + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-marathi_topic_all_doc_mr.md b/docs/_posts/ahmedlone127/2024-09-26-marathi_topic_all_doc_mr.md new file mode 100644 index 00000000000000..57f28027ecce78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-marathi_topic_all_doc_mr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Marathi marathi_topic_all_doc BertForSequenceClassification from l3cube-pune +author: John Snow Labs +name: marathi_topic_all_doc +date: 2024-09-26 +tags: [mr, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: mr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marathi_topic_all_doc` is a Marathi model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marathi_topic_all_doc_mr_5.5.0_3.0_1727366116577.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marathi_topic_all_doc_mr_5.5.0_3.0_1727366116577.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("marathi_topic_all_doc","mr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("marathi_topic_all_doc", "mr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marathi_topic_all_doc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|mr| +|Size:|892.9 MB| + +## References + +https://huggingface.co/l3cube-pune/marathi-topic-all-doc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-marker_associations_snp_binary_base_en.md b/docs/_posts/ahmedlone127/2024-09-26-marker_associations_snp_binary_base_en.md new file mode 100644 index 00000000000000..0bc464f2a2834e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-marker_associations_snp_binary_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English marker_associations_snp_binary_base BertForSequenceClassification from jambo +author: John Snow Labs +name: marker_associations_snp_binary_base +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marker_associations_snp_binary_base` is a English model originally trained by jambo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marker_associations_snp_binary_base_en_5.5.0_3.0_1727349708847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marker_associations_snp_binary_base_en_5.5.0_3.0_1727349708847.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("marker_associations_snp_binary_base","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("marker_associations_snp_binary_base", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marker_associations_snp_binary_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.4 MB| + +## References + +https://huggingface.co/jambo/marker-associations-snp-binary-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-marker_associations_snp_binary_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-marker_associations_snp_binary_base_pipeline_en.md new file mode 100644 index 00000000000000..bc5e9b6c699945 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-marker_associations_snp_binary_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English marker_associations_snp_binary_base_pipeline pipeline BertForSequenceClassification from jambo +author: John Snow Labs +name: marker_associations_snp_binary_base_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marker_associations_snp_binary_base_pipeline` is a English model originally trained by jambo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marker_associations_snp_binary_base_pipeline_en_5.5.0_3.0_1727349731543.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marker_associations_snp_binary_base_pipeline_en_5.5.0_3.0_1727349731543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marker_associations_snp_binary_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marker_associations_snp_binary_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marker_associations_snp_binary_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.4 MB| + +## References + +https://huggingface.co/jambo/marker-associations-snp-binary-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-master_bert_seq_training_model_en.md b/docs/_posts/ahmedlone127/2024-09-26-master_bert_seq_training_model_en.md new file mode 100644 index 00000000000000..d45171c7d58ba8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-master_bert_seq_training_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English master_bert_seq_training_model BertForSequenceClassification from Brecon +author: John Snow Labs +name: master_bert_seq_training_model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`master_bert_seq_training_model` is a English model originally trained by Brecon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/master_bert_seq_training_model_en_5.5.0_3.0_1727337158193.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/master_bert_seq_training_model_en_5.5.0_3.0_1727337158193.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("master_bert_seq_training_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("master_bert_seq_training_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|master_bert_seq_training_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Brecon/master_bert_seq_training_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-mcn_english_smm4h_en.md b/docs/_posts/ahmedlone127/2024-09-26-mcn_english_smm4h_en.md new file mode 100644 index 00000000000000..b03cf51aac695d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-mcn_english_smm4h_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mcn_english_smm4h BertForSequenceClassification from olastor +author: John Snow Labs +name: mcn_english_smm4h +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mcn_english_smm4h` is a English model originally trained by olastor. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mcn_english_smm4h_en_5.5.0_3.0_1727377049619.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mcn_english_smm4h_en_5.5.0_3.0_1727377049619.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("mcn_english_smm4h","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mcn_english_smm4h", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mcn_english_smm4h| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/olastor/mcn-en-smm4h \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-memo_bert_wsd_old_da.md b/docs/_posts/ahmedlone127/2024-09-26-memo_bert_wsd_old_da.md new file mode 100644 index 00000000000000..7cac6b46313aca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-memo_bert_wsd_old_da.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Danish memo_bert_wsd_old BertForSequenceClassification from yemen2016 +author: John Snow Labs +name: memo_bert_wsd_old +date: 2024-09-26 +tags: [da, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: da +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`memo_bert_wsd_old` is a Danish model originally trained by yemen2016. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/memo_bert_wsd_old_da_5.5.0_3.0_1727322417259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/memo_bert_wsd_old_da_5.5.0_3.0_1727322417259.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("memo_bert_wsd_old","da") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("memo_bert_wsd_old", "da") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|memo_bert_wsd_old| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|da| +|Size:|410.3 MB| + +## References + +https://huggingface.co/yemen2016/MeMo-BERT-WSD_old \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-mgc_5epchs_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-mgc_5epchs_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..1272c413dcb50b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-mgc_5epchs_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mgc_5epchs_bert_base_uncased_pipeline pipeline BertForSequenceClassification from PiceTRP +author: John Snow Labs +name: mgc_5epchs_bert_base_uncased_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mgc_5epchs_bert_base_uncased_pipeline` is a English model originally trained by PiceTRP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mgc_5epchs_bert_base_uncased_pipeline_en_5.5.0_3.0_1727377496000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mgc_5epchs_bert_base_uncased_pipeline_en_5.5.0_3.0_1727377496000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mgc_5epchs_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mgc_5epchs_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mgc_5epchs_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/PiceTRP/mgc_5epchs_bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-mi_super_modelo_omega4lpha_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-mi_super_modelo_omega4lpha_pipeline_en.md new file mode 100644 index 00000000000000..fb88b6abc2818d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-mi_super_modelo_omega4lpha_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mi_super_modelo_omega4lpha_pipeline pipeline BertForSequenceClassification from omega4lpha +author: John Snow Labs +name: mi_super_modelo_omega4lpha_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mi_super_modelo_omega4lpha_pipeline` is a English model originally trained by omega4lpha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mi_super_modelo_omega4lpha_pipeline_en_5.5.0_3.0_1727334723161.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mi_super_modelo_omega4lpha_pipeline_en_5.5.0_3.0_1727334723161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mi_super_modelo_omega4lpha_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mi_super_modelo_omega4lpha_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mi_super_modelo_omega4lpha_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/omega4lpha/mi-super-modelo + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-mnd_tweetevalbert_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-mnd_tweetevalbert_model_pipeline_en.md new file mode 100644 index 00000000000000..e9169ff043cbaf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-mnd_tweetevalbert_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mnd_tweetevalbert_model_pipeline pipeline BertForSequenceClassification from barbieheimer +author: John Snow Labs +name: mnd_tweetevalbert_model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mnd_tweetevalbert_model_pipeline` is a English model originally trained by barbieheimer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mnd_tweetevalbert_model_pipeline_en_5.5.0_3.0_1727360045307.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mnd_tweetevalbert_model_pipeline_en_5.5.0_3.0_1727360045307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mnd_tweetevalbert_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mnd_tweetevalbert_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mnd_tweetevalbert_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/barbieheimer/MND_TweetEvalBert_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-mobilebert_uncased_title2genre_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-mobilebert_uncased_title2genre_pipeline_en.md new file mode 100644 index 00000000000000..50f35817fce47f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-mobilebert_uncased_title2genre_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mobilebert_uncased_title2genre_pipeline pipeline BertForSequenceClassification from BEE-spoke-data +author: John Snow Labs +name: mobilebert_uncased_title2genre_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_uncased_title2genre_pipeline` is a English model originally trained by BEE-spoke-data. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_title2genre_pipeline_en_5.5.0_3.0_1727348563526.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_title2genre_pipeline_en_5.5.0_3.0_1727348563526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mobilebert_uncased_title2genre_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mobilebert_uncased_title2genre_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mobilebert_uncased_title2genre_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|92.6 MB| + +## References + +https://huggingface.co/BEE-spoke-data/mobilebert-uncased-title2genre + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-mod4team5_en.md b/docs/_posts/ahmedlone127/2024-09-26-mod4team5_en.md new file mode 100644 index 00000000000000..c8865af62714a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-mod4team5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mod4team5 BertForSequenceClassification from WyattMiller +author: John Snow Labs +name: mod4team5 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mod4team5` is a English model originally trained by WyattMiller. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mod4team5_en_5.5.0_3.0_1727346783889.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mod4team5_en_5.5.0_3.0_1727346783889.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("mod4team5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mod4team5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mod4team5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/WyattMiller/Mod4Team5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-model_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-model_2_pipeline_en.md new file mode 100644 index 00000000000000..18c4bb7af89c22 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-model_2_pipeline_en.md @@ -0,0 +1,72 @@ +--- +layout: model +title: English model_2_pipeline pipeline DistilBertForTokenClassification from anirudhramoo +author: John Snow Labs +name: model_2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_2_pipeline` is a English model originally trained by anirudhramoo. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_2_pipeline_en_5.5.0_3.0_1727390496883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_2_pipeline_en_5.5.0_3.0_1727390496883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("model_2_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("model_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +References + +https://huggingface.co/anirudhramoo/model_2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-model_imdb_bert_base_en.md b/docs/_posts/ahmedlone127/2024-09-26-model_imdb_bert_base_en.md new file mode 100644 index 00000000000000..197a1e63879222 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-model_imdb_bert_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English model_imdb_bert_base BertForSequenceClassification from Kudod +author: John Snow Labs +name: model_imdb_bert_base +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_imdb_bert_base` is a English model originally trained by Kudod. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_imdb_bert_base_en_5.5.0_3.0_1727386658268.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_imdb_bert_base_en_5.5.0_3.0_1727386658268.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("model_imdb_bert_base","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model_imdb_bert_base", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_imdb_bert_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.8 MB| + +## References + +https://huggingface.co/Kudod/model_IMDB_bert_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-model_imdb_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-model_imdb_bert_base_pipeline_en.md new file mode 100644 index 00000000000000..2fc1aac0a3b4b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-model_imdb_bert_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_imdb_bert_base_pipeline pipeline BertForSequenceClassification from Kudod +author: John Snow Labs +name: model_imdb_bert_base_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_imdb_bert_base_pipeline` is a English model originally trained by Kudod. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_imdb_bert_base_pipeline_en_5.5.0_3.0_1727386691490.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_imdb_bert_base_pipeline_en_5.5.0_3.0_1727386691490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_imdb_bert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_imdb_bert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_imdb_bert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|627.8 MB| + +## References + +https://huggingface.co/Kudod/model_IMDB_bert_base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-model_nimmyhbas_en.md b/docs/_posts/ahmedlone127/2024-09-26-model_nimmyhbas_en.md new file mode 100644 index 00000000000000..dc849bf9771b6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-model_nimmyhbas_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English model_nimmyhbas BertForSequenceClassification from NimmyhBas +author: John Snow Labs +name: model_nimmyhbas +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_nimmyhbas` is a English model originally trained by NimmyhBas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_nimmyhbas_en_5.5.0_3.0_1727372801192.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_nimmyhbas_en_5.5.0_3.0_1727372801192.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("model_nimmyhbas","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model_nimmyhbas", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_nimmyhbas| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NimmyhBas/Model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-model_nimmyhbas_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-model_nimmyhbas_pipeline_en.md new file mode 100644 index 00000000000000..796eb4a3fc9bb9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-model_nimmyhbas_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_nimmyhbas_pipeline pipeline BertForSequenceClassification from NimmyhBas +author: John Snow Labs +name: model_nimmyhbas_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_nimmyhbas_pipeline` is a English model originally trained by NimmyhBas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_nimmyhbas_pipeline_en_5.5.0_3.0_1727372865333.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_nimmyhbas_pipeline_en_5.5.0_3.0_1727372865333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_nimmyhbas_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_nimmyhbas_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_nimmyhbas_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NimmyhBas/Model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-movie_genre_classifier_omid_d_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-movie_genre_classifier_omid_d_pipeline_en.md new file mode 100644 index 00000000000000..5abd05d7d2db84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-movie_genre_classifier_omid_d_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English movie_genre_classifier_omid_d_pipeline pipeline BertForSequenceClassification from omid-d +author: John Snow Labs +name: movie_genre_classifier_omid_d_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_genre_classifier_omid_d_pipeline` is a English model originally trained by omid-d. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_genre_classifier_omid_d_pipeline_en_5.5.0_3.0_1727373756048.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_genre_classifier_omid_d_pipeline_en_5.5.0_3.0_1727373756048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("movie_genre_classifier_omid_d_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("movie_genre_classifier_omid_d_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|movie_genre_classifier_omid_d_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/omid-d/Movie_Genre_Classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-movie_genre_prediction_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-26-movie_genre_prediction_bert_base_uncased_en.md new file mode 100644 index 00000000000000..076dce39315c4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-movie_genre_prediction_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English movie_genre_prediction_bert_base_uncased BertForSequenceClassification from zayedupal +author: John Snow Labs +name: movie_genre_prediction_bert_base_uncased +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_genre_prediction_bert_base_uncased` is a English model originally trained by zayedupal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_genre_prediction_bert_base_uncased_en_5.5.0_3.0_1727390469239.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_genre_prediction_bert_base_uncased_en_5.5.0_3.0_1727390469239.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("movie_genre_prediction_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("movie_genre_prediction_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|movie_genre_prediction_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/zayedupal/movie-genre-prediction_bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-movie_genre_prediction_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-movie_genre_prediction_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..9a1478d3faef1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-movie_genre_prediction_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English movie_genre_prediction_bert_base_uncased_pipeline pipeline BertForSequenceClassification from zayedupal +author: John Snow Labs +name: movie_genre_prediction_bert_base_uncased_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`movie_genre_prediction_bert_base_uncased_pipeline` is a English model originally trained by zayedupal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/movie_genre_prediction_bert_base_uncased_pipeline_en_5.5.0_3.0_1727390491101.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/movie_genre_prediction_bert_base_uncased_pipeline_en_5.5.0_3.0_1727390491101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("movie_genre_prediction_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("movie_genre_prediction_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|movie_genre_prediction_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/zayedupal/movie-genre-prediction_bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-moviebertreview_sentimentprediction_model_afia_manubea_en.md b/docs/_posts/ahmedlone127/2024-09-26-moviebertreview_sentimentprediction_model_afia_manubea_en.md new file mode 100644 index 00000000000000..edbca28272b57b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-moviebertreview_sentimentprediction_model_afia_manubea_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English moviebertreview_sentimentprediction_model_afia_manubea BertForSequenceClassification from Afia-manubea +author: John Snow Labs +name: moviebertreview_sentimentprediction_model_afia_manubea +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`moviebertreview_sentimentprediction_model_afia_manubea` is a English model originally trained by Afia-manubea. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/moviebertreview_sentimentprediction_model_afia_manubea_en_5.5.0_3.0_1727322686702.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/moviebertreview_sentimentprediction_model_afia_manubea_en_5.5.0_3.0_1727322686702.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("moviebertreview_sentimentprediction_model_afia_manubea","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("moviebertreview_sentimentprediction_model_afia_manubea", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|moviebertreview_sentimentprediction_model_afia_manubea| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Afia-manubea/MovieBertReview-SentimentPrediction-Model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-moviebertreview_sentimentprediction_model_kabanda18_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-moviebertreview_sentimentprediction_model_kabanda18_pipeline_en.md new file mode 100644 index 00000000000000..846faf9df5d8e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-moviebertreview_sentimentprediction_model_kabanda18_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English moviebertreview_sentimentprediction_model_kabanda18_pipeline pipeline BertForSequenceClassification from KABANDA18 +author: John Snow Labs +name: moviebertreview_sentimentprediction_model_kabanda18_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`moviebertreview_sentimentprediction_model_kabanda18_pipeline` is a English model originally trained by KABANDA18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/moviebertreview_sentimentprediction_model_kabanda18_pipeline_en_5.5.0_3.0_1727341489189.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/moviebertreview_sentimentprediction_model_kabanda18_pipeline_en_5.5.0_3.0_1727341489189.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("moviebertreview_sentimentprediction_model_kabanda18_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("moviebertreview_sentimentprediction_model_kabanda18_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|moviebertreview_sentimentprediction_model_kabanda18_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/KABANDA18/MovieBertReview-SentimentPrediction-Model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-multi2convai_quality_english_bert_en.md b/docs/_posts/ahmedlone127/2024-09-26-multi2convai_quality_english_bert_en.md new file mode 100644 index 00000000000000..7392a9cf58a5b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-multi2convai_quality_english_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English multi2convai_quality_english_bert BertForSequenceClassification from inovex +author: John Snow Labs +name: multi2convai_quality_english_bert +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi2convai_quality_english_bert` is a English model originally trained by inovex. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi2convai_quality_english_bert_en_5.5.0_3.0_1727379402577.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi2convai_quality_english_bert_en_5.5.0_3.0_1727379402577.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("multi2convai_quality_english_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("multi2convai_quality_english_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi2convai_quality_english_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/inovex/multi2convai-quality-en-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-multi2convai_quality_english_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-multi2convai_quality_english_bert_pipeline_en.md new file mode 100644 index 00000000000000..6452170f6f3882 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-multi2convai_quality_english_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English multi2convai_quality_english_bert_pipeline pipeline BertForSequenceClassification from inovex +author: John Snow Labs +name: multi2convai_quality_english_bert_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multi2convai_quality_english_bert_pipeline` is a English model originally trained by inovex. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multi2convai_quality_english_bert_pipeline_en_5.5.0_3.0_1727379441148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multi2convai_quality_english_bert_pipeline_en_5.5.0_3.0_1727379441148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("multi2convai_quality_english_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("multi2convai_quality_english_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multi2convai_quality_english_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/inovex/multi2convai-quality-en-bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-mus_promoter_finetuned_lora_bert_base_t2t_en.md b/docs/_posts/ahmedlone127/2024-09-26-mus_promoter_finetuned_lora_bert_base_t2t_en.md new file mode 100644 index 00000000000000..9082eab21f070c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-mus_promoter_finetuned_lora_bert_base_t2t_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mus_promoter_finetuned_lora_bert_base_t2t BertForSequenceClassification from LiukG +author: John Snow Labs +name: mus_promoter_finetuned_lora_bert_base_t2t +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mus_promoter_finetuned_lora_bert_base_t2t` is a English model originally trained by LiukG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mus_promoter_finetuned_lora_bert_base_t2t_en_5.5.0_3.0_1727323560215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mus_promoter_finetuned_lora_bert_base_t2t_en_5.5.0_3.0_1727323560215.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("mus_promoter_finetuned_lora_bert_base_t2t","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mus_promoter_finetuned_lora_bert_base_t2t", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mus_promoter_finetuned_lora_bert_base_t2t| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|322.1 MB| + +## References + +https://huggingface.co/LiukG/mus_promoter-finetuned-lora-bert-base-t2t \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding40model_en.md b/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding40model_en.md new file mode 100644 index 00000000000000..fb5e7e4e855592 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding40model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_agnews_padding40model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_agnews_padding40model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_agnews_padding40model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding40model_en_5.5.0_3.0_1727373403227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding40model_en_5.5.0_3.0_1727373403227.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("n_bert_agnews_padding40model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_agnews_padding40model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_agnews_padding40model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Realgon/N_bert_agnews_padding40model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding60model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding60model_pipeline_en.md new file mode 100644 index 00000000000000..053bbcfdfe2830 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding60model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_bert_agnews_padding60model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_agnews_padding60model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_agnews_padding60model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding60model_pipeline_en_5.5.0_3.0_1727384233851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding60model_pipeline_en_5.5.0_3.0_1727384233851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_bert_agnews_padding60model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_bert_agnews_padding60model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_agnews_padding60model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Realgon/N_bert_agnews_padding60model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding80model_en.md b/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding80model_en.md new file mode 100644 index 00000000000000..4087aed241c0ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-n_bert_agnews_padding80model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_agnews_padding80model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_agnews_padding80model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_agnews_padding80model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding80model_en_5.5.0_3.0_1727370977552.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding80model_en_5.5.0_3.0_1727370977552.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("n_bert_agnews_padding80model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_agnews_padding80model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_agnews_padding80model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Realgon/N_bert_agnews_padding80model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-n_bert_sst5_padding50model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-n_bert_sst5_padding50model_pipeline_en.md new file mode 100644 index 00000000000000..b44d01d273e68e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-n_bert_sst5_padding50model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_bert_sst5_padding50model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_sst5_padding50model_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_sst5_padding50model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding50model_pipeline_en_5.5.0_3.0_1727349101412.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding50model_pipeline_en_5.5.0_3.0_1727349101412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_bert_sst5_padding50model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_bert_sst5_padding50model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_sst5_padding50model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Realgon/N_bert_sst5_padding50model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-n_bert_sst5_padding70model_en.md b/docs/_posts/ahmedlone127/2024-09-26-n_bert_sst5_padding70model_en.md new file mode 100644 index 00000000000000..d9901ef5966b12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-n_bert_sst5_padding70model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_sst5_padding70model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_sst5_padding70model +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_sst5_padding70model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding70model_en_5.5.0_3.0_1727355062689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding70model_en_5.5.0_3.0_1727355062689.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("n_bert_sst5_padding70model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_sst5_padding70model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_sst5_padding70model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Realgon/N_bert_sst5_padding70model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-namedescrbert_en.md b/docs/_posts/ahmedlone127/2024-09-26-namedescrbert_en.md new file mode 100644 index 00000000000000..5eb02ef6923472 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-namedescrbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English namedescrbert BertForSequenceClassification from madgnome +author: John Snow Labs +name: namedescrbert +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`namedescrbert` is a English model originally trained by madgnome. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/namedescrbert_en_5.5.0_3.0_1727391605047.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/namedescrbert_en_5.5.0_3.0_1727391605047.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("namedescrbert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("namedescrbert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|namedescrbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|669.1 MB| + +## References + +https://huggingface.co/madgnome/namedescrbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-namedescrbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-namedescrbert_pipeline_en.md new file mode 100644 index 00000000000000..bcd916aa669d07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-namedescrbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English namedescrbert_pipeline pipeline BertForSequenceClassification from madgnome +author: John Snow Labs +name: namedescrbert_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`namedescrbert_pipeline` is a English model originally trained by madgnome. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/namedescrbert_pipeline_en_5.5.0_3.0_1727391640560.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/namedescrbert_pipeline_en_5.5.0_3.0_1727391640560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("namedescrbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("namedescrbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|namedescrbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|669.1 MB| + +## References + +https://huggingface.co/madgnome/namedescrbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-newmodel_en.md b/docs/_posts/ahmedlone127/2024-09-26-newmodel_en.md new file mode 100644 index 00000000000000..c690a858d0f8cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-newmodel_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English newmodel BertEmbeddings from Dinithi +author: John Snow Labs +name: newmodel +date: 2024-09-26 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`newmodel` is a English model originally trained by Dinithi. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/newmodel_en_5.5.0_3.0_1727349706455.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/newmodel_en_5.5.0_3.0_1727349706455.zip){:.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 =BertEmbeddings.pretrained("newmodel","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 = BertEmbeddings + .pretrained("newmodel", "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:|newmodel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +References + +https://huggingface.co/Dinithi/NewModel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-news_sentimental_model_buy_neutral_sell_en.md b/docs/_posts/ahmedlone127/2024-09-26-news_sentimental_model_buy_neutral_sell_en.md new file mode 100644 index 00000000000000..90aaf3e6b33f9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-news_sentimental_model_buy_neutral_sell_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English news_sentimental_model_buy_neutral_sell BertForSequenceClassification from incredible45 +author: John Snow Labs +name: news_sentimental_model_buy_neutral_sell +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`news_sentimental_model_buy_neutral_sell` is a English model originally trained by incredible45. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/news_sentimental_model_buy_neutral_sell_en_5.5.0_3.0_1727348787127.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/news_sentimental_model_buy_neutral_sell_en_5.5.0_3.0_1727348787127.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("news_sentimental_model_buy_neutral_sell","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("news_sentimental_model_buy_neutral_sell", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|news_sentimental_model_buy_neutral_sell| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/incredible45/News-Sentimental-model-Buy-Neutral-Sell \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-news_sentimental_model_buy_neutral_sell_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-news_sentimental_model_buy_neutral_sell_pipeline_en.md new file mode 100644 index 00000000000000..b5c1e6f94bd71a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-news_sentimental_model_buy_neutral_sell_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English news_sentimental_model_buy_neutral_sell_pipeline pipeline BertForSequenceClassification from incredible45 +author: John Snow Labs +name: news_sentimental_model_buy_neutral_sell_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`news_sentimental_model_buy_neutral_sell_pipeline` is a English model originally trained by incredible45. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/news_sentimental_model_buy_neutral_sell_pipeline_en_5.5.0_3.0_1727348809193.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/news_sentimental_model_buy_neutral_sell_pipeline_en_5.5.0_3.0_1727348809193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("news_sentimental_model_buy_neutral_sell_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("news_sentimental_model_buy_neutral_sell_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|news_sentimental_model_buy_neutral_sell_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/incredible45/News-Sentimental-model-Buy-Neutral-Sell + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-nli_sts_klue_bert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-nli_sts_klue_bert_base_pipeline_en.md new file mode 100644 index 00000000000000..9d4c1dcfcb09a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-nli_sts_klue_bert_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nli_sts_klue_bert_base_pipeline pipeline BertForSequenceClassification from ys7yoo +author: John Snow Labs +name: nli_sts_klue_bert_base_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nli_sts_klue_bert_base_pipeline` is a English model originally trained by ys7yoo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nli_sts_klue_bert_base_pipeline_en_5.5.0_3.0_1727382007911.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nli_sts_klue_bert_base_pipeline_en_5.5.0_3.0_1727382007911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nli_sts_klue_bert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nli_sts_klue_bert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nli_sts_klue_bert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/ys7yoo/nli-sts_klue_bert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-nlp_task2_en.md b/docs/_posts/ahmedlone127/2024-09-26-nlp_task2_en.md new file mode 100644 index 00000000000000..b5045d0fbaa83d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-nlp_task2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nlp_task2 BertForSequenceClassification from guna-2222 +author: John Snow Labs +name: nlp_task2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_task2` is a English model originally trained by guna-2222. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_task2_en_5.5.0_3.0_1727372318665.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_task2_en_5.5.0_3.0_1727372318665.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("nlp_task2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("nlp_task2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_task2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/guna-2222/NLP_task2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-nlp_task2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-nlp_task2_pipeline_en.md new file mode 100644 index 00000000000000..d185dce4202424 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-nlp_task2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nlp_task2_pipeline pipeline BertForSequenceClassification from guna-2222 +author: John Snow Labs +name: nlp_task2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_task2_pipeline` is a English model originally trained by guna-2222. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_task2_pipeline_en_5.5.0_3.0_1727372340648.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_task2_pipeline_en_5.5.0_3.0_1727372340648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nlp_task2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nlp_task2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_task2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/guna-2222/NLP_task2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-nlp_taxonomy_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-26-nlp_taxonomy_classifier_en.md new file mode 100644 index 00000000000000..c067c27e622ed1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-nlp_taxonomy_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nlp_taxonomy_classifier BertForSequenceClassification from TimSchopf +author: John Snow Labs +name: nlp_taxonomy_classifier +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_taxonomy_classifier` is a English model originally trained by TimSchopf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_taxonomy_classifier_en_5.5.0_3.0_1727367027730.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_taxonomy_classifier_en_5.5.0_3.0_1727367027730.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("nlp_taxonomy_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("nlp_taxonomy_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_taxonomy_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.4 MB| + +## References + +https://huggingface.co/TimSchopf/nlp_taxonomy_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-odia_topic_all_doc_or.md b/docs/_posts/ahmedlone127/2024-09-26-odia_topic_all_doc_or.md new file mode 100644 index 00000000000000..dfc7297c137ab0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-odia_topic_all_doc_or.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Oriya (macrolanguage) odia_topic_all_doc BertForSequenceClassification from l3cube-pune +author: John Snow Labs +name: odia_topic_all_doc +date: 2024-09-26 +tags: [or, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: or +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`odia_topic_all_doc` is a Oriya (macrolanguage) model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/odia_topic_all_doc_or_5.5.0_3.0_1727369015043.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/odia_topic_all_doc_or_5.5.0_3.0_1727369015043.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("odia_topic_all_doc","or") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("odia_topic_all_doc", "or") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|odia_topic_all_doc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|or| +|Size:|892.6 MB| + +## References + +https://huggingface.co/l3cube-pune/odia-topic-all-doc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-opticalbert_abstract_classification_cased_en.md b/docs/_posts/ahmedlone127/2024-09-26-opticalbert_abstract_classification_cased_en.md new file mode 100644 index 00000000000000..57eb78c4970b25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-opticalbert_abstract_classification_cased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English opticalbert_abstract_classification_cased BertForSequenceClassification from opticalmaterials +author: John Snow Labs +name: opticalbert_abstract_classification_cased +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opticalbert_abstract_classification_cased` is a English model originally trained by opticalmaterials. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opticalbert_abstract_classification_cased_en_5.5.0_3.0_1727394437873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opticalbert_abstract_classification_cased_en_5.5.0_3.0_1727394437873.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("opticalbert_abstract_classification_cased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("opticalbert_abstract_classification_cased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opticalbert_abstract_classification_cased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.7 MB| + +## References + +https://huggingface.co/opticalmaterials/opticalbert_abstract_classification_cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-opticalbert_abstract_classification_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-opticalbert_abstract_classification_cased_pipeline_en.md new file mode 100644 index 00000000000000..f8b6c7dde5f172 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-opticalbert_abstract_classification_cased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English opticalbert_abstract_classification_cased_pipeline pipeline BertForSequenceClassification from opticalmaterials +author: John Snow Labs +name: opticalbert_abstract_classification_cased_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`opticalbert_abstract_classification_cased_pipeline` is a English model originally trained by opticalmaterials. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/opticalbert_abstract_classification_cased_pipeline_en_5.5.0_3.0_1727394458391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/opticalbert_abstract_classification_cased_pipeline_en_5.5.0_3.0_1727394458391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("opticalbert_abstract_classification_cased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("opticalbert_abstract_classification_cased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|opticalbert_abstract_classification_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.8 MB| + +## References + +https://huggingface.co/opticalmaterials/opticalbert_abstract_classification_cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-original_oomr_800_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-original_oomr_800_pipeline_en.md new file mode 100644 index 00000000000000..1d55a2784009cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-original_oomr_800_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English original_oomr_800_pipeline pipeline BertForSequenceClassification from abbassix +author: John Snow Labs +name: original_oomr_800_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`original_oomr_800_pipeline` is a English model originally trained by abbassix. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/original_oomr_800_pipeline_en_5.5.0_3.0_1727384202721.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/original_oomr_800_pipeline_en_5.5.0_3.0_1727384202721.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("original_oomr_800_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("original_oomr_800_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|original_oomr_800_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/abbassix/original_oomr_800 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-out_glue_mrpc_en.md b/docs/_posts/ahmedlone127/2024-09-26-out_glue_mrpc_en.md new file mode 100644 index 00000000000000..6c9c452909ff97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-out_glue_mrpc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English out_glue_mrpc BertForSequenceClassification from Tural +author: John Snow Labs +name: out_glue_mrpc +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`out_glue_mrpc` is a English model originally trained by Tural. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/out_glue_mrpc_en_5.5.0_3.0_1727380367896.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/out_glue_mrpc_en_5.5.0_3.0_1727380367896.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("out_glue_mrpc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("out_glue_mrpc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|out_glue_mrpc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Tural/out-glue-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-out_glue_mrpc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-out_glue_mrpc_pipeline_en.md new file mode 100644 index 00000000000000..9e2d5f5df80aef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-out_glue_mrpc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English out_glue_mrpc_pipeline pipeline BertForSequenceClassification from Tural +author: John Snow Labs +name: out_glue_mrpc_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`out_glue_mrpc_pipeline` is a English model originally trained by Tural. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/out_glue_mrpc_pipeline_en_5.5.0_3.0_1727380390477.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/out_glue_mrpc_pipeline_en_5.5.0_3.0_1727380390477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("out_glue_mrpc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("out_glue_mrpc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|out_glue_mrpc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Tural/out-glue-mrpc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-out_glue_sst2_en.md b/docs/_posts/ahmedlone127/2024-09-26-out_glue_sst2_en.md new file mode 100644 index 00000000000000..0bc74bb314f7a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-out_glue_sst2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English out_glue_sst2 BertForSequenceClassification from Tural +author: John Snow Labs +name: out_glue_sst2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`out_glue_sst2` is a English model originally trained by Tural. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/out_glue_sst2_en_5.5.0_3.0_1727324207285.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/out_glue_sst2_en_5.5.0_3.0_1727324207285.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("out_glue_sst2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("out_glue_sst2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|out_glue_sst2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Tural/out-glue-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-paraphrase_bert_portuguese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-paraphrase_bert_portuguese_pipeline_en.md new file mode 100644 index 00000000000000..14f07ade85b4fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-paraphrase_bert_portuguese_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English paraphrase_bert_portuguese_pipeline pipeline BertForSequenceClassification from erickrribeiro +author: John Snow Labs +name: paraphrase_bert_portuguese_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`paraphrase_bert_portuguese_pipeline` is a English model originally trained by erickrribeiro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_bert_portuguese_pipeline_en_5.5.0_3.0_1727356373514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_bert_portuguese_pipeline_en_5.5.0_3.0_1727356373514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("paraphrase_bert_portuguese_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("paraphrase_bert_portuguese_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_bert_portuguese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/erickrribeiro/paraphrase-bert-portuguese + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-paraphrase_detection_bert_en.md b/docs/_posts/ahmedlone127/2024-09-26-paraphrase_detection_bert_en.md new file mode 100644 index 00000000000000..e9276573b4c02a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-paraphrase_detection_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English paraphrase_detection_bert BertForSequenceClassification from Isezerano +author: John Snow Labs +name: paraphrase_detection_bert +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_detection_bert` is a English model originally trained by Isezerano. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/paraphrase_detection_bert_en_5.5.0_3.0_1727340743587.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/paraphrase_detection_bert_en_5.5.0_3.0_1727340743587.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("paraphrase_detection_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("paraphrase_detection_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|paraphrase_detection_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Isezerano/paraphrase_detection_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-parlbert_classify_climate_v01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-parlbert_classify_climate_v01_pipeline_en.md new file mode 100644 index 00000000000000..e52493f7b40355 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-parlbert_classify_climate_v01_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English parlbert_classify_climate_v01_pipeline pipeline BertForSequenceClassification from liserman +author: John Snow Labs +name: parlbert_classify_climate_v01_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parlbert_classify_climate_v01_pipeline` is a English model originally trained by liserman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/parlbert_classify_climate_v01_pipeline_en_5.5.0_3.0_1727309784757.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parlbert_classify_climate_v01_pipeline_en_5.5.0_3.0_1727309784757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("parlbert_classify_climate_v01_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("parlbert_classify_climate_v01_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|parlbert_classify_climate_v01_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/liserman/parlbert_classify_climate_v01 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-parsbert_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-parsbert_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..14da9193fb6e30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-parsbert_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English parsbert_finetuned_pipeline pipeline BertForSequenceClassification from mohammad-osoolian +author: John Snow Labs +name: parsbert_finetuned_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parsbert_finetuned_pipeline` is a English model originally trained by mohammad-osoolian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/parsbert_finetuned_pipeline_en_5.5.0_3.0_1727323919364.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parsbert_finetuned_pipeline_en_5.5.0_3.0_1727323919364.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("parsbert_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("parsbert_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|parsbert_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|608.7 MB| + +## References + +https://huggingface.co/mohammad-osoolian/parsbert-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-partypress_monolingual_spain_es.md b/docs/_posts/ahmedlone127/2024-09-26-partypress_monolingual_spain_es.md new file mode 100644 index 00000000000000..02ba51bf25c23f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-partypress_monolingual_spain_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish partypress_monolingual_spain BertForSequenceClassification from partypress +author: John Snow Labs +name: partypress_monolingual_spain +date: 2024-09-26 +tags: [es, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`partypress_monolingual_spain` is a Castilian, Spanish model originally trained by partypress. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/partypress_monolingual_spain_es_5.5.0_3.0_1727385882788.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/partypress_monolingual_spain_es_5.5.0_3.0_1727385882788.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("partypress_monolingual_spain","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("partypress_monolingual_spain", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|partypress_monolingual_spain| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.9 MB| + +## References + +https://huggingface.co/partypress/partypress-monolingual-spain \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-partypress_monolingual_spain_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-26-partypress_monolingual_spain_pipeline_es.md new file mode 100644 index 00000000000000..35b0fa26f08d7b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-partypress_monolingual_spain_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish partypress_monolingual_spain_pipeline pipeline BertForSequenceClassification from partypress +author: John Snow Labs +name: partypress_monolingual_spain_pipeline +date: 2024-09-26 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`partypress_monolingual_spain_pipeline` is a Castilian, Spanish model originally trained by partypress. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/partypress_monolingual_spain_pipeline_es_5.5.0_3.0_1727385906225.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/partypress_monolingual_spain_pipeline_es_5.5.0_3.0_1727385906225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("partypress_monolingual_spain_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("partypress_monolingual_spain_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|partypress_monolingual_spain_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|412.0 MB| + +## References + +https://huggingface.co/partypress/partypress-monolingual-spain + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-pft_clf_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-26-pft_clf_finetuned_en.md new file mode 100644 index 00000000000000..f24d04fe14bfa3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-pft_clf_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English pft_clf_finetuned BertForSequenceClassification from Faezeh-gholamrezaie +author: John Snow Labs +name: pft_clf_finetuned +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pft_clf_finetuned` is a English model originally trained by Faezeh-gholamrezaie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pft_clf_finetuned_en_5.5.0_3.0_1727381667754.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pft_clf_finetuned_en_5.5.0_3.0_1727381667754.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("pft_clf_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("pft_clf_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pft_clf_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|443.8 MB| + +## References + +https://huggingface.co/Faezeh-gholamrezaie/pft-clf-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-pft_clf_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-pft_clf_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..28deb3982a6c24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-pft_clf_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English pft_clf_finetuned_pipeline pipeline BertForSequenceClassification from Faezeh-gholamrezaie +author: John Snow Labs +name: pft_clf_finetuned_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pft_clf_finetuned_pipeline` is a English model originally trained by Faezeh-gholamrezaie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pft_clf_finetuned_pipeline_en_5.5.0_3.0_1727381697608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pft_clf_finetuned_pipeline_en_5.5.0_3.0_1727381697608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pft_clf_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pft_clf_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pft_clf_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|443.8 MB| + +## References + +https://huggingface.co/Faezeh-gholamrezaie/pft-clf-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_eusojk_en.md b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_eusojk_en.md new file mode 100644 index 00000000000000..52a88ec704d562 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_eusojk_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_eusojk BertForSequenceClassification from eusojk +author: John Snow Labs +name: phrasebank_sentiment_analysis_eusojk +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_eusojk` is a English model originally trained by eusojk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_eusojk_en_5.5.0_3.0_1727387110776.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_eusojk_en_5.5.0_3.0_1727387110776.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("phrasebank_sentiment_analysis_eusojk","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("phrasebank_sentiment_analysis_eusojk", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_eusojk| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/eusojk/phrasebank-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_eusojk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_eusojk_pipeline_en.md new file mode 100644 index 00000000000000..638afe1a1854f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_eusojk_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_eusojk_pipeline pipeline BertForSequenceClassification from eusojk +author: John Snow Labs +name: phrasebank_sentiment_analysis_eusojk_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_eusojk_pipeline` is a English model originally trained by eusojk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_eusojk_pipeline_en_5.5.0_3.0_1727387133532.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_eusojk_pipeline_en_5.5.0_3.0_1727387133532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_eusojk_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_eusojk_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_eusojk_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/eusojk/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_guilima5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_guilima5_pipeline_en.md new file mode 100644 index 00000000000000..14dc0f18587750 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_guilima5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_guilima5_pipeline pipeline BertForSequenceClassification from guilima5 +author: John Snow Labs +name: phrasebank_sentiment_analysis_guilima5_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_guilima5_pipeline` is a English model originally trained by guilima5. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_guilima5_pipeline_en_5.5.0_3.0_1727373633546.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_guilima5_pipeline_en_5.5.0_3.0_1727373633546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_guilima5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_guilima5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_guilima5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/guilima5/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_phusun_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_phusun_pipeline_en.md new file mode 100644 index 00000000000000..278a155a6510f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_phusun_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_phusun_pipeline pipeline BertForSequenceClassification from phusun +author: John Snow Labs +name: phrasebank_sentiment_analysis_phusun_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_phusun_pipeline` is a English model originally trained by phusun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_phusun_pipeline_en_5.5.0_3.0_1727372905825.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_phusun_pipeline_en_5.5.0_3.0_1727372905825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_phusun_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_phusun_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_phusun_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/phusun/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_priyabrata018_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_priyabrata018_pipeline_en.md new file mode 100644 index 00000000000000..5cbe182ba62055 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_priyabrata018_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_priyabrata018_pipeline pipeline BertForSequenceClassification from Priyabrata018 +author: John Snow Labs +name: phrasebank_sentiment_analysis_priyabrata018_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_priyabrata018_pipeline` is a English model originally trained by Priyabrata018. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_priyabrata018_pipeline_en_5.5.0_3.0_1727336851907.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_priyabrata018_pipeline_en_5.5.0_3.0_1727336851907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_priyabrata018_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_priyabrata018_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_priyabrata018_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Priyabrata018/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_snowc2023_en.md b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_snowc2023_en.md new file mode 100644 index 00000000000000..b502b88aadecce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_snowc2023_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_snowc2023 BertForSequenceClassification from snowc2023 +author: John Snow Labs +name: phrasebank_sentiment_analysis_snowc2023 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_snowc2023` is a English model originally trained by snowc2023. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_snowc2023_en_5.5.0_3.0_1727342597733.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_snowc2023_en_5.5.0_3.0_1727342597733.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("phrasebank_sentiment_analysis_snowc2023","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("phrasebank_sentiment_analysis_snowc2023", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_snowc2023| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/snowc2023/phrasebank-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_zyoscovits_en.md b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_zyoscovits_en.md new file mode 100644 index 00000000000000..de0b0af01cef4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_zyoscovits_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_zyoscovits BertForSequenceClassification from zyoscovits +author: John Snow Labs +name: phrasebank_sentiment_analysis_zyoscovits +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_zyoscovits` is a English model originally trained by zyoscovits. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_zyoscovits_en_5.5.0_3.0_1727345647112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_zyoscovits_en_5.5.0_3.0_1727345647112.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("phrasebank_sentiment_analysis_zyoscovits","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("phrasebank_sentiment_analysis_zyoscovits", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_zyoscovits| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/zyoscovits/phrasebank-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_zyoscovits_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_zyoscovits_pipeline_en.md new file mode 100644 index 00000000000000..fc507ff7e0d352 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-phrasebank_sentiment_analysis_zyoscovits_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_zyoscovits_pipeline pipeline BertForSequenceClassification from zyoscovits +author: John Snow Labs +name: phrasebank_sentiment_analysis_zyoscovits_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_zyoscovits_pipeline` is a English model originally trained by zyoscovits. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_zyoscovits_pipeline_en_5.5.0_3.0_1727345668596.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_zyoscovits_pipeline_en_5.5.0_3.0_1727345668596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_zyoscovits_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_zyoscovits_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_zyoscovits_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/zyoscovits/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-pretrain1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-pretrain1_pipeline_en.md new file mode 100644 index 00000000000000..b4b7a1d7a4cfa8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-pretrain1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English pretrain1_pipeline pipeline BertForSequenceClassification from fcx-kilig +author: John Snow Labs +name: pretrain1_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pretrain1_pipeline` is a English model originally trained by fcx-kilig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrain1_pipeline_en_5.5.0_3.0_1727376095905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrain1_pipeline_en_5.5.0_3.0_1727376095905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pretrain1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pretrain1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pretrain1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/fcx-kilig/pretrain1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-priv_ftc_en.md b/docs/_posts/ahmedlone127/2024-09-26-priv_ftc_en.md new file mode 100644 index 00000000000000..88869f148e5ee9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-priv_ftc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English priv_ftc BertForSequenceClassification from arjunth2001 +author: John Snow Labs +name: priv_ftc +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`priv_ftc` is a English model originally trained by arjunth2001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/priv_ftc_en_5.5.0_3.0_1727309730623.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/priv_ftc_en_5.5.0_3.0_1727309730623.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("priv_ftc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("priv_ftc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|priv_ftc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/arjunth2001/priv_ftc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-priv_ftc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-priv_ftc_pipeline_en.md new file mode 100644 index 00000000000000..3391d9ec031835 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-priv_ftc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English priv_ftc_pipeline pipeline BertForSequenceClassification from arjunth2001 +author: John Snow Labs +name: priv_ftc_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`priv_ftc_pipeline` is a English model originally trained by arjunth2001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/priv_ftc_pipeline_en_5.5.0_3.0_1727309752746.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/priv_ftc_pipeline_en_5.5.0_3.0_1727309752746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("priv_ftc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("priv_ftc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|priv_ftc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/arjunth2001/priv_ftc + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-ptv1_bert_large_uncased_sst2_en.md b/docs/_posts/ahmedlone127/2024-09-26-ptv1_bert_large_uncased_sst2_en.md new file mode 100644 index 00000000000000..e6d4efe6153243 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-ptv1_bert_large_uncased_sst2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ptv1_bert_large_uncased_sst2 BertForSequenceClassification from AudreyTrungNguyen +author: John Snow Labs +name: ptv1_bert_large_uncased_sst2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptv1_bert_large_uncased_sst2` is a English model originally trained by AudreyTrungNguyen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptv1_bert_large_uncased_sst2_en_5.5.0_3.0_1727388283775.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptv1_bert_large_uncased_sst2_en_5.5.0_3.0_1727388283775.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("ptv1_bert_large_uncased_sst2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ptv1_bert_large_uncased_sst2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ptv1_bert_large_uncased_sst2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/AudreyTrungNguyen/ptv1-bert-large-uncased-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-ptv2_bert_large_uncased_sst2_en.md b/docs/_posts/ahmedlone127/2024-09-26-ptv2_bert_large_uncased_sst2_en.md new file mode 100644 index 00000000000000..654d3f83b76095 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-ptv2_bert_large_uncased_sst2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ptv2_bert_large_uncased_sst2 BertForSequenceClassification from AudreyTrungNguyen +author: John Snow Labs +name: ptv2_bert_large_uncased_sst2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ptv2_bert_large_uncased_sst2` is a English model originally trained by AudreyTrungNguyen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ptv2_bert_large_uncased_sst2_en_5.5.0_3.0_1727317239896.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ptv2_bert_large_uncased_sst2_en_5.5.0_3.0_1727317239896.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("ptv2_bert_large_uncased_sst2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ptv2_bert_large_uncased_sst2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ptv2_bert_large_uncased_sst2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/AudreyTrungNguyen/ptv2-bert-large-uncased-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-q06_kaggle_bertbasecased_en.md b/docs/_posts/ahmedlone127/2024-09-26-q06_kaggle_bertbasecased_en.md new file mode 100644 index 00000000000000..e269436c9990a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-q06_kaggle_bertbasecased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English q06_kaggle_bertbasecased BertForSequenceClassification from wallacenpj +author: John Snow Labs +name: q06_kaggle_bertbasecased +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`q06_kaggle_bertbasecased` is a English model originally trained by wallacenpj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/q06_kaggle_bertbasecased_en_5.5.0_3.0_1727384490230.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/q06_kaggle_bertbasecased_en_5.5.0_3.0_1727384490230.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("q06_kaggle_bertbasecased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("q06_kaggle_bertbasecased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|q06_kaggle_bertbasecased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/wallacenpj/q06_kaggle_bertbasecased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-qd_tweet_convbert_base_turkish_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-qd_tweet_convbert_base_turkish_pipeline_en.md new file mode 100644 index 00000000000000..0d0f54afe158aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-qd_tweet_convbert_base_turkish_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English qd_tweet_convbert_base_turkish_pipeline pipeline BertForSequenceClassification from Izzet +author: John Snow Labs +name: qd_tweet_convbert_base_turkish_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qd_tweet_convbert_base_turkish_pipeline` is a English model originally trained by Izzet. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qd_tweet_convbert_base_turkish_pipeline_en_5.5.0_3.0_1727352695414.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qd_tweet_convbert_base_turkish_pipeline_en_5.5.0_3.0_1727352695414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("qd_tweet_convbert_base_turkish_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("qd_tweet_convbert_base_turkish_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qd_tweet_convbert_base_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|402.3 MB| + +## References + +https://huggingface.co/Izzet/qd_tweet_convbert-base-turkish + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-question_detection_user_utter_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-question_detection_user_utter_pipeline_en.md new file mode 100644 index 00000000000000..93f679ecb82d30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-question_detection_user_utter_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English question_detection_user_utter_pipeline pipeline BertForSequenceClassification from huaen +author: John Snow Labs +name: question_detection_user_utter_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`question_detection_user_utter_pipeline` is a English model originally trained by huaen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/question_detection_user_utter_pipeline_en_5.5.0_3.0_1727318979972.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/question_detection_user_utter_pipeline_en_5.5.0_3.0_1727318979972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("question_detection_user_utter_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("question_detection_user_utter_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|question_detection_user_utter_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/huaen/question_detection_user_utter + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-r2anker_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-r2anker_pipeline_en.md new file mode 100644 index 00000000000000..e90b40acb97ad3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-r2anker_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English r2anker_pipeline pipeline BertForSequenceClassification from YCZhou +author: John Snow Labs +name: r2anker_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`r2anker_pipeline` is a English model originally trained by YCZhou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/r2anker_pipeline_en_5.5.0_3.0_1727395194379.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/r2anker_pipeline_en_5.5.0_3.0_1727395194379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("r2anker_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("r2anker_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|r2anker_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/YCZhou/R2ANKER + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_base_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_base_pipeline_ru.md new file mode 100644 index 00000000000000..ad213580dffc29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_base_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian response_quality_classifier_base_pipeline pipeline BertForSequenceClassification from t-bank-ai +author: John Snow Labs +name: response_quality_classifier_base_pipeline +date: 2024-09-26 +tags: [ru, open_source, pipeline, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`response_quality_classifier_base_pipeline` is a Russian model originally trained by t-bank-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/response_quality_classifier_base_pipeline_ru_5.5.0_3.0_1727360046916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/response_quality_classifier_base_pipeline_ru_5.5.0_3.0_1727360046916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("response_quality_classifier_base_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("response_quality_classifier_base_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|response_quality_classifier_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|666.7 MB| + +## References + +https://huggingface.co/t-bank-ai/response-quality-classifier-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_tiny_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_tiny_pipeline_ru.md new file mode 100644 index 00000000000000..960d5734995fe4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_tiny_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian response_quality_classifier_tiny_pipeline pipeline BertForSequenceClassification from t-bank-ai +author: John Snow Labs +name: response_quality_classifier_tiny_pipeline +date: 2024-09-26 +tags: [ru, open_source, pipeline, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`response_quality_classifier_tiny_pipeline` is a Russian model originally trained by t-bank-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/response_quality_classifier_tiny_pipeline_ru_5.5.0_3.0_1727386759700.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/response_quality_classifier_tiny_pipeline_ru_5.5.0_3.0_1727386759700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("response_quality_classifier_tiny_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("response_quality_classifier_tiny_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|response_quality_classifier_tiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|109.9 MB| + +## References + +https://huggingface.co/t-bank-ai/response-quality-classifier-tiny + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_tiny_ru.md b/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_tiny_ru.md new file mode 100644 index 00000000000000..b6c1e716c4827c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-response_quality_classifier_tiny_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian response_quality_classifier_tiny BertForSequenceClassification from t-bank-ai +author: John Snow Labs +name: response_quality_classifier_tiny +date: 2024-09-26 +tags: [ru, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`response_quality_classifier_tiny` is a Russian model originally trained by t-bank-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/response_quality_classifier_tiny_ru_5.5.0_3.0_1727386754218.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/response_quality_classifier_tiny_ru_5.5.0_3.0_1727386754218.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("response_quality_classifier_tiny","ru") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("response_quality_classifier_tiny", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|response_quality_classifier_tiny| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|109.9 MB| + +## References + +https://huggingface.co/t-bank-ai/response-quality-classifier-tiny \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-results_profoz_en.md b/docs/_posts/ahmedlone127/2024-09-26-results_profoz_en.md new file mode 100644 index 00000000000000..8122e221a50343 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-results_profoz_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English results_profoz BertForSequenceClassification from profoz +author: John Snow Labs +name: results_profoz +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_profoz` is a English model originally trained by profoz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_profoz_en_5.5.0_3.0_1727378691935.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_profoz_en_5.5.0_3.0_1727378691935.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("results_profoz","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("results_profoz", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|results_profoz| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.8 MB| + +## References + +https://huggingface.co/profoz/results \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-results_profoz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-results_profoz_pipeline_en.md new file mode 100644 index 00000000000000..54896080ed9378 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-results_profoz_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English results_profoz_pipeline pipeline BertForSequenceClassification from profoz +author: John Snow Labs +name: results_profoz_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_profoz_pipeline` is a English model originally trained by profoz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_profoz_pipeline_en_5.5.0_3.0_1727378718369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_profoz_pipeline_en_5.5.0_3.0_1727378718369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("results_profoz_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("results_profoz_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|results_profoz_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|413.8 MB| + +## References + +https://huggingface.co/profoz/results + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-reviewusefulness_multiclassclassification_de.md b/docs/_posts/ahmedlone127/2024-09-26-reviewusefulness_multiclassclassification_de.md new file mode 100644 index 00000000000000..02ac81d7930055 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-reviewusefulness_multiclassclassification_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German reviewusefulness_multiclassclassification BertForSequenceClassification from jorgeortizv +author: John Snow Labs +name: reviewusefulness_multiclassclassification +date: 2024-09-26 +tags: [de, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reviewusefulness_multiclassclassification` is a German model originally trained by jorgeortizv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reviewusefulness_multiclassclassification_de_5.5.0_3.0_1727375075122.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reviewusefulness_multiclassclassification_de_5.5.0_3.0_1727375075122.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("reviewusefulness_multiclassclassification","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("reviewusefulness_multiclassclassification", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reviewusefulness_multiclassclassification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|409.1 MB| + +## References + +https://huggingface.co/jorgeortizv/reviewUsefulness-multiclassClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-reviewusefulness_multiclassclassification_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-26-reviewusefulness_multiclassclassification_pipeline_de.md new file mode 100644 index 00000000000000..3a69b7e7e2504e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-reviewusefulness_multiclassclassification_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German reviewusefulness_multiclassclassification_pipeline pipeline BertForSequenceClassification from jorgeortizv +author: John Snow Labs +name: reviewusefulness_multiclassclassification_pipeline +date: 2024-09-26 +tags: [de, open_source, pipeline, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`reviewusefulness_multiclassclassification_pipeline` is a German model originally trained by jorgeortizv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/reviewusefulness_multiclassclassification_pipeline_de_5.5.0_3.0_1727375097140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/reviewusefulness_multiclassclassification_pipeline_de_5.5.0_3.0_1727375097140.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("reviewusefulness_multiclassclassification_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("reviewusefulness_multiclassclassification_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|reviewusefulness_multiclassclassification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|409.1 MB| + +## References + +https://huggingface.co/jorgeortizv/reviewUsefulness-multiclassClassification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-rewardmodel_nicholaskluge_en.md b/docs/_posts/ahmedlone127/2024-09-26-rewardmodel_nicholaskluge_en.md new file mode 100644 index 00000000000000..ea4d11536415f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-rewardmodel_nicholaskluge_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English rewardmodel_nicholaskluge BertForSequenceClassification from nicholasKluge +author: John Snow Labs +name: rewardmodel_nicholaskluge +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rewardmodel_nicholaskluge` is a English model originally trained by nicholasKluge. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rewardmodel_nicholaskluge_en_5.5.0_3.0_1727388066876.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rewardmodel_nicholaskluge_en_5.5.0_3.0_1727388066876.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("rewardmodel_nicholaskluge","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rewardmodel_nicholaskluge", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rewardmodel_nicholaskluge| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/nicholasKluge/RewardModel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-ruberttiny_attr_name_add_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-ruberttiny_attr_name_add_pipeline_en.md new file mode 100644 index 00000000000000..5a32ebe7bd89fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-ruberttiny_attr_name_add_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ruberttiny_attr_name_add_pipeline pipeline BertForSequenceClassification from Shakhovak +author: John Snow Labs +name: ruberttiny_attr_name_add_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ruberttiny_attr_name_add_pipeline` is a English model originally trained by Shakhovak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ruberttiny_attr_name_add_pipeline_en_5.5.0_3.0_1727309185693.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ruberttiny_attr_name_add_pipeline_en_5.5.0_3.0_1727309185693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ruberttiny_attr_name_add_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ruberttiny_attr_name_add_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ruberttiny_attr_name_add_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|109.5 MB| + +## References + +https://huggingface.co/Shakhovak/ruBertTiny_attr_name_add + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sabert_spanish_fake_news_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-26-sabert_spanish_fake_news_pipeline_es.md new file mode 100644 index 00000000000000..49b9f044d7c965 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sabert_spanish_fake_news_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish sabert_spanish_fake_news_pipeline pipeline BertForSequenceClassification from VerificadoProfesional +author: John Snow Labs +name: sabert_spanish_fake_news_pipeline +date: 2024-09-26 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sabert_spanish_fake_news_pipeline` is a Castilian, Spanish model originally trained by VerificadoProfesional. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sabert_spanish_fake_news_pipeline_es_5.5.0_3.0_1727308821811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sabert_spanish_fake_news_pipeline_es_5.5.0_3.0_1727308821811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sabert_spanish_fake_news_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sabert_spanish_fake_news_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sabert_spanish_fake_news_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|411.9 MB| + +## References + +https://huggingface.co/VerificadoProfesional/SaBERT-Spanish-Fake-News + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sagemaker_bert_base_arabic_arsas_en.md b/docs/_posts/ahmedlone127/2024-09-26-sagemaker_bert_base_arabic_arsas_en.md new file mode 100644 index 00000000000000..a7dd57106b1db0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sagemaker_bert_base_arabic_arsas_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sagemaker_bert_base_arabic_arsas BertForSequenceClassification from Osaleh +author: John Snow Labs +name: sagemaker_bert_base_arabic_arsas +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sagemaker_bert_base_arabic_arsas` is a English model originally trained by Osaleh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sagemaker_bert_base_arabic_arsas_en_5.5.0_3.0_1727311699899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sagemaker_bert_base_arabic_arsas_en_5.5.0_3.0_1727311699899.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("sagemaker_bert_base_arabic_arsas","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sagemaker_bert_base_arabic_arsas", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sagemaker_bert_base_arabic_arsas| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.2 MB| + +## References + +https://huggingface.co/Osaleh/sagemaker-bert-base-arabic-ArSAS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sagemaker_bert_base_intent1018_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-sagemaker_bert_base_intent1018_pipeline_en.md new file mode 100644 index 00000000000000..7064438c1f1573 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sagemaker_bert_base_intent1018_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sagemaker_bert_base_intent1018_pipeline pipeline BertForSequenceClassification from Osaleh +author: John Snow Labs +name: sagemaker_bert_base_intent1018_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sagemaker_bert_base_intent1018_pipeline` is a English model originally trained by Osaleh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sagemaker_bert_base_intent1018_pipeline_en_5.5.0_3.0_1727374622234.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sagemaker_bert_base_intent1018_pipeline_en_5.5.0_3.0_1727374622234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sagemaker_bert_base_intent1018_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sagemaker_bert_base_intent1018_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sagemaker_bert_base_intent1018_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.4 MB| + +## References + +https://huggingface.co/Osaleh/sagemaker-bert-base-intent1018 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sarcasm_detection_bert_base_uncased_newdata_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-sarcasm_detection_bert_base_uncased_newdata_pipeline_en.md new file mode 100644 index 00000000000000..001dcebee71b85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sarcasm_detection_bert_base_uncased_newdata_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sarcasm_detection_bert_base_uncased_newdata_pipeline pipeline BertForSequenceClassification from jkhan447 +author: John Snow Labs +name: sarcasm_detection_bert_base_uncased_newdata_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sarcasm_detection_bert_base_uncased_newdata_pipeline` is a English model originally trained by jkhan447. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sarcasm_detection_bert_base_uncased_newdata_pipeline_en_5.5.0_3.0_1727334964245.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sarcasm_detection_bert_base_uncased_newdata_pipeline_en_5.5.0_3.0_1727334964245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sarcasm_detection_bert_base_uncased_newdata_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sarcasm_detection_bert_base_uncased_newdata_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sarcasm_detection_bert_base_uncased_newdata_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jkhan447/sarcasm-detection-Bert-base-uncased-newdata + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sbert_russian_sentiment_krnd_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-09-26-sbert_russian_sentiment_krnd_pipeline_ru.md new file mode 100644 index 00000000000000..2b664e68454ca5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sbert_russian_sentiment_krnd_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian sbert_russian_sentiment_krnd_pipeline pipeline BertForSequenceClassification from sismetanin +author: John Snow Labs +name: sbert_russian_sentiment_krnd_pipeline +date: 2024-09-26 +tags: [ru, open_source, pipeline, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sbert_russian_sentiment_krnd_pipeline` is a Russian model originally trained by sismetanin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sbert_russian_sentiment_krnd_pipeline_ru_5.5.0_3.0_1727382354457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sbert_russian_sentiment_krnd_pipeline_ru_5.5.0_3.0_1727382354457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sbert_russian_sentiment_krnd_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sbert_russian_sentiment_krnd_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sbert_russian_sentiment_krnd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|1.6 GB| + +## References + +https://huggingface.co/sismetanin/sbert-ru-sentiment-krnd + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_rte_model_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_rte_model_bert_base_uncased_en.md new file mode 100644 index 00000000000000..e59d2822fe051d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_rte_model_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English scenario_tcr_data_glue_rte_model_bert_base_uncased BertForSequenceClassification from haryoaw +author: John Snow Labs +name: scenario_tcr_data_glue_rte_model_bert_base_uncased +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_glue_rte_model_bert_base_uncased` is a English model originally trained by haryoaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_rte_model_bert_base_uncased_en_5.5.0_3.0_1727342421439.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_rte_model_bert_base_uncased_en_5.5.0_3.0_1727342421439.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("scenario_tcr_data_glue_rte_model_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scenario_tcr_data_glue_rte_model_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_tcr_data_glue_rte_model_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/haryoaw/scenario-TCR-data-glue-rte-model-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..d273ff378ea0a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline pipeline BertForSequenceClassification from haryoaw +author: John Snow Labs +name: scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline` is a English model originally trained by haryoaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727342443410.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727342443410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_tcr_data_glue_rte_model_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/haryoaw/scenario-TCR-data-glue-rte-model-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..1c2d95a9255f41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline pipeline BertForSequenceClassification from haryoaw +author: John Snow Labs +name: scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline` is a English model originally trained by haryoaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727341046131.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727341046131.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_tcr_data_glue_stsb_model_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/haryoaw/scenario-TCR-data-glue-stsb-model-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-scibert_nlp4sg_en.md b/docs/_posts/ahmedlone127/2024-09-26-scibert_nlp4sg_en.md new file mode 100644 index 00000000000000..23cb4512bc8b34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-scibert_nlp4sg_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English scibert_nlp4sg BertForSequenceClassification from feradauto +author: John Snow Labs +name: scibert_nlp4sg +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_nlp4sg` is a English model originally trained by feradauto. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scibert_nlp4sg_en_5.5.0_3.0_1727373269819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scibert_nlp4sg_en_5.5.0_3.0_1727373269819.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("scibert_nlp4sg","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scibert_nlp4sg", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scibert_nlp4sg| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/feradauto/scibert_nlp4sg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-scibert_sdg_cased_zo_up_en.md b/docs/_posts/ahmedlone127/2024-09-26-scibert_sdg_cased_zo_up_en.md new file mode 100644 index 00000000000000..587083d25aca83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-scibert_sdg_cased_zo_up_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English scibert_sdg_cased_zo_up BertForSequenceClassification from dvdblk +author: John Snow Labs +name: scibert_sdg_cased_zo_up +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_sdg_cased_zo_up` is a English model originally trained by dvdblk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scibert_sdg_cased_zo_up_en_5.5.0_3.0_1727389069247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scibert_sdg_cased_zo_up_en_5.5.0_3.0_1727389069247.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("scibert_sdg_cased_zo_up","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scibert_sdg_cased_zo_up", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scibert_sdg_cased_zo_up| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/dvdblk/scibert_sdg_cased_zo-up \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_rte_en.md b/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_rte_en.md new file mode 100644 index 00000000000000..16f430e987daa5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_rte_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sead_l_6_h_256_a_8_rte BertForSequenceClassification from C5i +author: John Snow Labs +name: sead_l_6_h_256_a_8_rte +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sead_l_6_h_256_a_8_rte` is a English model originally trained by C5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sead_l_6_h_256_a_8_rte_en_5.5.0_3.0_1727393154671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sead_l_6_h_256_a_8_rte_en_5.5.0_3.0_1727393154671.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("sead_l_6_h_256_a_8_rte","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sead_l_6_h_256_a_8_rte", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sead_l_6_h_256_a_8_rte| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|47.3 MB| + +## References + +https://huggingface.co/C5i/SEAD-L-6_H-256_A-8-rte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_rte_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_rte_pipeline_en.md new file mode 100644 index 00000000000000..037d55a21eaf74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_rte_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sead_l_6_h_256_a_8_rte_pipeline pipeline BertForSequenceClassification from C5i +author: John Snow Labs +name: sead_l_6_h_256_a_8_rte_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sead_l_6_h_256_a_8_rte_pipeline` is a English model originally trained by C5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sead_l_6_h_256_a_8_rte_pipeline_en_5.5.0_3.0_1727393157760.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sead_l_6_h_256_a_8_rte_pipeline_en_5.5.0_3.0_1727393157760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sead_l_6_h_256_a_8_rte_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sead_l_6_h_256_a_8_rte_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sead_l_6_h_256_a_8_rte_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|47.3 MB| + +## References + +https://huggingface.co/C5i/SEAD-L-6_H-256_A-8-rte + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_sst2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_sst2_pipeline_en.md new file mode 100644 index 00000000000000..54071da58ad55e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_256_a_8_sst2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sead_l_6_h_256_a_8_sst2_pipeline pipeline BertForSequenceClassification from C5i +author: John Snow Labs +name: sead_l_6_h_256_a_8_sst2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sead_l_6_h_256_a_8_sst2_pipeline` is a English model originally trained by C5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sead_l_6_h_256_a_8_sst2_pipeline_en_5.5.0_3.0_1727359119417.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sead_l_6_h_256_a_8_sst2_pipeline_en_5.5.0_3.0_1727359119417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sead_l_6_h_256_a_8_sst2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sead_l_6_h_256_a_8_sst2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sead_l_6_h_256_a_8_sst2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|47.3 MB| + +## References + +https://huggingface.co/C5i/SEAD-L-6_H-256_A-8-sst2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_384_a_12_sst2_en.md b/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_384_a_12_sst2_en.md new file mode 100644 index 00000000000000..1b8c85cb8462dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sead_l_6_h_384_a_12_sst2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sead_l_6_h_384_a_12_sst2 BertForSequenceClassification from C5i +author: John Snow Labs +name: sead_l_6_h_384_a_12_sst2 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sead_l_6_h_384_a_12_sst2` is a English model originally trained by C5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sead_l_6_h_384_a_12_sst2_en_5.5.0_3.0_1727390625914.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sead_l_6_h_384_a_12_sst2_en_5.5.0_3.0_1727390625914.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("sead_l_6_h_384_a_12_sst2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sead_l_6_h_384_a_12_sst2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sead_l_6_h_384_a_12_sst2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|84.2 MB| + +## References + +https://huggingface.co/C5i/SEAD-L-6_H-384_A-12-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sentimen_analysis_yelp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-sentimen_analysis_yelp_pipeline_en.md new file mode 100644 index 00000000000000..96251f62e40ae9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sentimen_analysis_yelp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentimen_analysis_yelp_pipeline pipeline BertForSequenceClassification from Imran1 +author: John Snow Labs +name: sentimen_analysis_yelp_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentimen_analysis_yelp_pipeline` is a English model originally trained by Imran1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentimen_analysis_yelp_pipeline_en_5.5.0_3.0_1727343179340.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentimen_analysis_yelp_pipeline_en_5.5.0_3.0_1727343179340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentimen_analysis_yelp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentimen_analysis_yelp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentimen_analysis_yelp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Imran1/sentimen_analysis_yelp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sentiment_analysis_freceerwin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-sentiment_analysis_freceerwin_pipeline_en.md new file mode 100644 index 00000000000000..700f45909b0e94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sentiment_analysis_freceerwin_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentiment_analysis_freceerwin_pipeline pipeline BertForSequenceClassification from Freceerwin +author: John Snow Labs +name: sentiment_analysis_freceerwin_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_analysis_freceerwin_pipeline` is a English model originally trained by Freceerwin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_freceerwin_pipeline_en_5.5.0_3.0_1727379487598.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_freceerwin_pipeline_en_5.5.0_3.0_1727379487598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentiment_analysis_freceerwin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentiment_analysis_freceerwin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_analysis_freceerwin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|608.8 MB| + +## References + +https://huggingface.co/Freceerwin/sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sentiment_analysis_task_1_en.md b/docs/_posts/ahmedlone127/2024-09-26-sentiment_analysis_task_1_en.md new file mode 100644 index 00000000000000..f4d9137023a287 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sentiment_analysis_task_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentiment_analysis_task_1 BertForSequenceClassification from ABHISHEKMONU2001 +author: John Snow Labs +name: sentiment_analysis_task_1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_analysis_task_1` is a English model originally trained by ABHISHEKMONU2001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_task_1_en_5.5.0_3.0_1727317772354.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_task_1_en_5.5.0_3.0_1727317772354.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("sentiment_analysis_task_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_analysis_task_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_analysis_task_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ABHISHEKMONU2001/Sentiment_Analysis_Task_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sentiment_model_saagie_en.md b/docs/_posts/ahmedlone127/2024-09-26-sentiment_model_saagie_en.md new file mode 100644 index 00000000000000..9fb2542737cf4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sentiment_model_saagie_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentiment_model_saagie BertForSequenceClassification from TeamResearch +author: John Snow Labs +name: sentiment_model_saagie +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_model_saagie` is a English model originally trained by TeamResearch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_model_saagie_en_5.5.0_3.0_1727311375516.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_model_saagie_en_5.5.0_3.0_1727311375516.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("sentiment_model_saagie","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_model_saagie", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_model_saagie| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/TeamResearch/sentiment-model-saagie \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sentimental_en.md b/docs/_posts/ahmedlone127/2024-09-26-sentimental_en.md new file mode 100644 index 00000000000000..c80c80c1239bb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sentimental_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentimental BertForSequenceClassification from vikaskapur +author: John Snow Labs +name: sentimental +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentimental` is a English model originally trained by vikaskapur. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentimental_en_5.5.0_3.0_1727372816275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentimental_en_5.5.0_3.0_1727372816275.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("sentimental","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentimental", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentimental| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/vikaskapur/sentimental \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sentimental_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-sentimental_pipeline_en.md new file mode 100644 index 00000000000000..e66ee4103599f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sentimental_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentimental_pipeline pipeline BertForSequenceClassification from vikaskapur +author: John Snow Labs +name: sentimental_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentimental_pipeline` is a English model originally trained by vikaskapur. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentimental_pipeline_en_5.5.0_3.0_1727372837968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentimental_pipeline_en_5.5.0_3.0_1727372837968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentimental_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentimental_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentimental_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/vikaskapur/sentimental + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-simnonym_pt.md b/docs/_posts/ahmedlone127/2024-09-26-simnonym_pt.md new file mode 100644 index 00000000000000..3f02cab480199f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-simnonym_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese simnonym BertForSequenceClassification from lrds-code +author: John Snow Labs +name: simnonym +date: 2024-09-26 +tags: [pt, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simnonym` is a Portuguese model originally trained by lrds-code. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simnonym_pt_5.5.0_3.0_1727388310504.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simnonym_pt_5.5.0_3.0_1727388310504.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("simnonym","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("simnonym", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|simnonym| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.1 MB| + +## References + +https://huggingface.co/lrds-code/simnonym \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-simple_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-simple_classification_pipeline_en.md new file mode 100644 index 00000000000000..37556c6909e91a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-simple_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English simple_classification_pipeline pipeline BertForSequenceClassification from mjavadmt +author: John Snow Labs +name: simple_classification_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`simple_classification_pipeline` is a English model originally trained by mjavadmt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/simple_classification_pipeline_en_5.5.0_3.0_1727342461562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/simple_classification_pipeline_en_5.5.0_3.0_1727342461562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("simple_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("simple_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|simple_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/mjavadmt/simple_classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-snli_w_premise_100k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-snli_w_premise_100k_pipeline_en.md new file mode 100644 index 00000000000000..69c6b1c7dfa159 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-snli_w_premise_100k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English snli_w_premise_100k_pipeline pipeline BertForSequenceClassification from grace-pro +author: John Snow Labs +name: snli_w_premise_100k_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`snli_w_premise_100k_pipeline` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snli_w_premise_100k_pipeline_en_5.5.0_3.0_1727340200283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snli_w_premise_100k_pipeline_en_5.5.0_3.0_1727340200283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("snli_w_premise_100k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("snli_w_premise_100k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|snli_w_premise_100k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/snli_w_premise_100k + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_10e_en.md b/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_10e_en.md new file mode 100644 index 00000000000000..219f67ef0364d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_10e_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spam_small_data_bert_base_10e BertForSequenceClassification from nlpotato +author: John Snow Labs +name: spam_small_data_bert_base_10e +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spam_small_data_bert_base_10e` is a English model originally trained by nlpotato. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spam_small_data_bert_base_10e_en_5.5.0_3.0_1727373480908.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spam_small_data_bert_base_10e_en_5.5.0_3.0_1727373480908.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("spam_small_data_bert_base_10e","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("spam_small_data_bert_base_10e", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spam_small_data_bert_base_10e| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/nlpotato/spam-small-data-bert-base-10e \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_3e_en.md b/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_3e_en.md new file mode 100644 index 00000000000000..1afe3fb5b8a57e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_3e_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English spam_small_data_bert_base_3e BertForSequenceClassification from nlpotato +author: John Snow Labs +name: spam_small_data_bert_base_3e +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spam_small_data_bert_base_3e` is a English model originally trained by nlpotato. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spam_small_data_bert_base_3e_en_5.5.0_3.0_1727372123277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spam_small_data_bert_base_3e_en_5.5.0_3.0_1727372123277.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("spam_small_data_bert_base_3e","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("spam_small_data_bert_base_3e", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spam_small_data_bert_base_3e| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/nlpotato/spam-small-data-bert-base-3e \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_3e_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_3e_pipeline_en.md new file mode 100644 index 00000000000000..77c0a0012d9b57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-spam_small_data_bert_base_3e_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English spam_small_data_bert_base_3e_pipeline pipeline BertForSequenceClassification from nlpotato +author: John Snow Labs +name: spam_small_data_bert_base_3e_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spam_small_data_bert_base_3e_pipeline` is a English model originally trained by nlpotato. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spam_small_data_bert_base_3e_pipeline_en_5.5.0_3.0_1727372147556.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spam_small_data_bert_base_3e_pipeline_en_5.5.0_3.0_1727372147556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spam_small_data_bert_base_3e_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spam_small_data_bert_base_3e_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spam_small_data_bert_base_3e_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/nlpotato/spam-small-data-bert-base-3e + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-spanish_offensive_language_bert_base_spanish_wwm_cased_es.md b/docs/_posts/ahmedlone127/2024-09-26-spanish_offensive_language_bert_base_spanish_wwm_cased_es.md new file mode 100644 index 00000000000000..8d224899c288d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-spanish_offensive_language_bert_base_spanish_wwm_cased_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish spanish_offensive_language_bert_base_spanish_wwm_cased BertForSequenceClassification from jorgeortizfuentes +author: John Snow Labs +name: spanish_offensive_language_bert_base_spanish_wwm_cased +date: 2024-09-26 +tags: [es, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_offensive_language_bert_base_spanish_wwm_cased` is a Castilian, Spanish model originally trained by jorgeortizfuentes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_offensive_language_bert_base_spanish_wwm_cased_es_5.5.0_3.0_1727380700468.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_offensive_language_bert_base_spanish_wwm_cased_es_5.5.0_3.0_1727380700468.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("spanish_offensive_language_bert_base_spanish_wwm_cased","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("spanish_offensive_language_bert_base_spanish_wwm_cased", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_offensive_language_bert_base_spanish_wwm_cased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/jorgeortizfuentes/spanish-offensive-language-bert-base-spanish-wwm-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sst_bert_base_uncased_cambridgeltl_en.md b/docs/_posts/ahmedlone127/2024-09-26-sst_bert_base_uncased_cambridgeltl_en.md new file mode 100644 index 00000000000000..a1823e6f3a4eef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sst_bert_base_uncased_cambridgeltl_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sst_bert_base_uncased_cambridgeltl BertForSequenceClassification from cambridgeltl +author: John Snow Labs +name: sst_bert_base_uncased_cambridgeltl +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sst_bert_base_uncased_cambridgeltl` is a English model originally trained by cambridgeltl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sst_bert_base_uncased_cambridgeltl_en_5.5.0_3.0_1727373264180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sst_bert_base_uncased_cambridgeltl_en_5.5.0_3.0_1727373264180.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("sst_bert_base_uncased_cambridgeltl","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sst_bert_base_uncased_cambridgeltl", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sst_bert_base_uncased_cambridgeltl| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cambridgeltl/sst_bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-sst_bert_base_uncased_cambridgeltl_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-sst_bert_base_uncased_cambridgeltl_pipeline_en.md new file mode 100644 index 00000000000000..38e9e68c44d914 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-sst_bert_base_uncased_cambridgeltl_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sst_bert_base_uncased_cambridgeltl_pipeline pipeline BertForSequenceClassification from cambridgeltl +author: John Snow Labs +name: sst_bert_base_uncased_cambridgeltl_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sst_bert_base_uncased_cambridgeltl_pipeline` is a English model originally trained by cambridgeltl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sst_bert_base_uncased_cambridgeltl_pipeline_en_5.5.0_3.0_1727373286005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sst_bert_base_uncased_cambridgeltl_pipeline_en_5.5.0_3.0_1727373286005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sst_bert_base_uncased_cambridgeltl_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sst_bert_base_uncased_cambridgeltl_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sst_bert_base_uncased_cambridgeltl_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cambridgeltl/sst_bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_en.md b/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_en.md new file mode 100644 index 00000000000000..cc1faf2ab61fb1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English stsb_tinybert_l_4_finetuned_auc_151221_top3_op1 BertForSequenceClassification from Katsiaryna +author: John Snow Labs +name: stsb_tinybert_l_4_finetuned_auc_151221_top3_op1 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stsb_tinybert_l_4_finetuned_auc_151221_top3_op1` is a English model originally trained by Katsiaryna. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_en_5.5.0_3.0_1727376536466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_en_5.5.0_3.0_1727376536466.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("stsb_tinybert_l_4_finetuned_auc_151221_top3_op1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("stsb_tinybert_l_4_finetuned_auc_151221_top3_op1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|stsb_tinybert_l_4_finetuned_auc_151221_top3_op1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Katsiaryna/stsb-TinyBERT-L-4-finetuned_auc_151221-top3_op1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline_en.md new file mode 100644 index 00000000000000..471fe3debc5640 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline pipeline BertForSequenceClassification from Katsiaryna +author: John Snow Labs +name: stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline` is a English model originally trained by Katsiaryna. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline_en_5.5.0_3.0_1727376539348.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline_en_5.5.0_3.0_1727376539348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|stsb_tinybert_l_4_finetuned_auc_151221_top3_op1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Katsiaryna/stsb-TinyBERT-L-4-finetuned_auc_151221-top3_op1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_40000_top3_bce_en.md b/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_40000_top3_bce_en.md new file mode 100644 index 00000000000000..83d38f1d23280c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-stsb_tinybert_l_4_finetuned_auc_40000_top3_bce_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English stsb_tinybert_l_4_finetuned_auc_40000_top3_bce BertForSequenceClassification from Katsiaryna +author: John Snow Labs +name: stsb_tinybert_l_4_finetuned_auc_40000_top3_bce +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`stsb_tinybert_l_4_finetuned_auc_40000_top3_bce` is a English model originally trained by Katsiaryna. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_40000_top3_bce_en_5.5.0_3.0_1727337832499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/stsb_tinybert_l_4_finetuned_auc_40000_top3_bce_en_5.5.0_3.0_1727337832499.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("stsb_tinybert_l_4_finetuned_auc_40000_top3_bce","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("stsb_tinybert_l_4_finetuned_auc_40000_top3_bce", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|stsb_tinybert_l_4_finetuned_auc_40000_top3_bce| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Katsiaryna/stsb-TinyBERT-L-4-finetuned_auc_40000-top3-BCE \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tai_1_1_tr.md b/docs/_posts/ahmedlone127/2024-09-26-tai_1_1_tr.md new file mode 100644 index 00000000000000..022a5965a0fab0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tai_1_1_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish tai_1_1 BertForSequenceClassification from yasarefe +author: John Snow Labs +name: tai_1_1 +date: 2024-09-26 +tags: [tr, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tai_1_1` is a Turkish model originally trained by yasarefe. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tai_1_1_tr_5.5.0_3.0_1727378769393.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tai_1_1_tr_5.5.0_3.0_1727378769393.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("tai_1_1","tr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tai_1_1", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tai_1_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|414.5 MB| + +## References + +https://huggingface.co/yasarefe/tai-1.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-test_trainer_dongxiaoxia194_en.md b/docs/_posts/ahmedlone127/2024-09-26-test_trainer_dongxiaoxia194_en.md new file mode 100644 index 00000000000000..0665b6cb3e26d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-test_trainer_dongxiaoxia194_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English test_trainer_dongxiaoxia194 BertForSequenceClassification from dongxiaoxia194 +author: John Snow Labs +name: test_trainer_dongxiaoxia194 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_trainer_dongxiaoxia194` is a English model originally trained by dongxiaoxia194. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_dongxiaoxia194_en_5.5.0_3.0_1727353381130.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_dongxiaoxia194_en_5.5.0_3.0_1727353381130.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("test_trainer_dongxiaoxia194","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("test_trainer_dongxiaoxia194", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_trainer_dongxiaoxia194| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/dongxiaoxia194/test-trainer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-test_trainer_imbalanced1_0_en.md b/docs/_posts/ahmedlone127/2024-09-26-test_trainer_imbalanced1_0_en.md new file mode 100644 index 00000000000000..eb32b3e13c2623 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-test_trainer_imbalanced1_0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English test_trainer_imbalanced1_0 BertForSequenceClassification from manatiw +author: John Snow Labs +name: test_trainer_imbalanced1_0 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_trainer_imbalanced1_0` is a English model originally trained by manatiw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_imbalanced1_0_en_5.5.0_3.0_1727391228958.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_imbalanced1_0_en_5.5.0_3.0_1727391228958.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("test_trainer_imbalanced1_0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("test_trainer_imbalanced1_0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_trainer_imbalanced1_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|144.3 MB| + +## References + +https://huggingface.co/manatiw/test-trainer-imbalanced1.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-text_classification_ziffir_en.md b/docs/_posts/ahmedlone127/2024-09-26-text_classification_ziffir_en.md new file mode 100644 index 00000000000000..0dc65926516c7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-text_classification_ziffir_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English text_classification_ziffir BertForSequenceClassification from ziffir +author: John Snow Labs +name: text_classification_ziffir +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classification_ziffir` is a English model originally trained by ziffir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classification_ziffir_en_5.5.0_3.0_1727371040973.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classification_ziffir_en_5.5.0_3.0_1727371040973.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("text_classification_ziffir","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("text_classification_ziffir", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|text_classification_ziffir| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ziffir/Text-Classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-text_emotion_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-26-text_emotion_classifier_en.md new file mode 100644 index 00000000000000..48f36f02956f86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-text_emotion_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English text_emotion_classifier BertForSequenceClassification from ahmetyaylalioglu +author: John Snow Labs +name: text_emotion_classifier +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_emotion_classifier` is a English model originally trained by ahmetyaylalioglu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_emotion_classifier_en_5.5.0_3.0_1727391355948.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_emotion_classifier_en_5.5.0_3.0_1727391355948.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("text_emotion_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("text_emotion_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|text_emotion_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ahmetyaylalioglu/text-emotion-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tibetan_bert_tncc_title_tsheg_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-tibetan_bert_tncc_title_tsheg_pipeline_en.md new file mode 100644 index 00000000000000..e7ad2ac7276654 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tibetan_bert_tncc_title_tsheg_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tibetan_bert_tncc_title_tsheg_pipeline pipeline BertForSequenceClassification from UTibetNLP +author: John Snow Labs +name: tibetan_bert_tncc_title_tsheg_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tibetan_bert_tncc_title_tsheg_pipeline` is a English model originally trained by UTibetNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tibetan_bert_tncc_title_tsheg_pipeline_en_5.5.0_3.0_1727352901777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tibetan_bert_tncc_title_tsheg_pipeline_en_5.5.0_3.0_1727352901777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tibetan_bert_tncc_title_tsheg_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tibetan_bert_tncc_title_tsheg_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tibetan_bert_tncc_title_tsheg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.8 MB| + +## References + +https://huggingface.co/UTibetNLP/tibetan-bert_tncc-title_tsheg + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_2401_en.md b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_2401_en.md new file mode 100644 index 00000000000000..9754608abf8dd2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_2401_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tiny_bert_2401 BertForSequenceClassification from gg-ai +author: John Snow Labs +name: tiny_bert_2401 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_2401` is a English model originally trained by gg-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_2401_en_5.5.0_3.0_1727383101133.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_2401_en_5.5.0_3.0_1727383101133.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("tiny_bert_2401","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_2401", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_2401| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|463.3 MB| + +## References + +https://huggingface.co/gg-ai/tiny-bert-2401 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_2401_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_2401_pipeline_en.md new file mode 100644 index 00000000000000..42b378931b81fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_2401_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tiny_bert_2401_pipeline pipeline BertForSequenceClassification from gg-ai +author: John Snow Labs +name: tiny_bert_2401_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_2401_pipeline` is a English model originally trained by gg-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_2401_pipeline_en_5.5.0_3.0_1727383125339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_2401_pipeline_en_5.5.0_3.0_1727383125339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tiny_bert_2401_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tiny_bert_2401_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_2401_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.4 MB| + +## References + +https://huggingface.co/gg-ai/tiny-bert-2401 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_base_bert_score_en.md b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_base_bert_score_en.md new file mode 100644 index 00000000000000..577f99d9b064a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_base_bert_score_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tiny_bert_base_bert_score BertForSequenceClassification from moussaKam +author: John Snow Labs +name: tiny_bert_base_bert_score +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_base_bert_score` is a English model originally trained by moussaKam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_base_bert_score_en_5.5.0_3.0_1727343334950.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_base_bert_score_en_5.5.0_3.0_1727343334950.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("tiny_bert_base_bert_score","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_base_bert_score", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_base_bert_score| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/moussaKam/tiny_bert-base_bert-score \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_base_bert_score_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_base_bert_score_pipeline_en.md new file mode 100644 index 00000000000000..9823062e5d6a64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_base_bert_score_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tiny_bert_base_bert_score_pipeline pipeline BertForSequenceClassification from moussaKam +author: John Snow Labs +name: tiny_bert_base_bert_score_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_base_bert_score_pipeline` is a English model originally trained by moussaKam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_base_bert_score_pipeline_en_5.5.0_3.0_1727343336113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_base_bert_score_pipeline_en_5.5.0_3.0_1727343336113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tiny_bert_base_bert_score_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tiny_bert_base_bert_score_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_base_bert_score_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/moussaKam/tiny_bert-base_bert-score + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_ranker_en.md b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_ranker_en.md new file mode 100644 index 00000000000000..c196538af0bfd5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tiny_bert_ranker_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tiny_bert_ranker BertForSequenceClassification from webis +author: John Snow Labs +name: tiny_bert_ranker +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_ranker` is a English model originally trained by webis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_ranker_en_5.5.0_3.0_1727376297309.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_ranker_en_5.5.0_3.0_1727376297309.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("tiny_bert_ranker","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_ranker", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_ranker| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.8 MB| + +## References + +https://huggingface.co/webis/tiny-bert-ranker \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tiny_random_debertaforsequenceclassification_hf_tiny_model_private_en.md b/docs/_posts/ahmedlone127/2024-09-26-tiny_random_debertaforsequenceclassification_hf_tiny_model_private_en.md new file mode 100644 index 00000000000000..92fb0c76667b8c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tiny_random_debertaforsequenceclassification_hf_tiny_model_private_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tiny_random_debertaforsequenceclassification_hf_tiny_model_private BertForSequenceClassification from hf-tiny-model-private +author: John Snow Labs +name: tiny_random_debertaforsequenceclassification_hf_tiny_model_private +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_random_debertaforsequenceclassification_hf_tiny_model_private` is a English model originally trained by hf-tiny-model-private. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_random_debertaforsequenceclassification_hf_tiny_model_private_en_5.5.0_3.0_1727369550328.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_random_debertaforsequenceclassification_hf_tiny_model_private_en_5.5.0_3.0_1727369550328.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("tiny_random_debertaforsequenceclassification_hf_tiny_model_private","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_random_debertaforsequenceclassification_hf_tiny_model_private", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_random_debertaforsequenceclassification_hf_tiny_model_private| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|350.1 KB| + +## References + +https://huggingface.co/hf-tiny-model-private/tiny-random-DebertaForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-topic_abstract_classification_en.md b/docs/_posts/ahmedlone127/2024-09-26-topic_abstract_classification_en.md new file mode 100644 index 00000000000000..892784fd409d16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-topic_abstract_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English topic_abstract_classification BertForSequenceClassification from Eitanli +author: John Snow Labs +name: topic_abstract_classification +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`topic_abstract_classification` is a English model originally trained by Eitanli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/topic_abstract_classification_en_5.5.0_3.0_1727312799104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/topic_abstract_classification_en_5.5.0_3.0_1727312799104.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("topic_abstract_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("topic_abstract_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|topic_abstract_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Eitanli/topic_abstract_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-toxic_en.md b/docs/_posts/ahmedlone127/2024-09-26-toxic_en.md new file mode 100644 index 00000000000000..fda256cb9f4ec3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-toxic_en.md @@ -0,0 +1,98 @@ +--- +layout: model +title: English toxic DistilBertForSequenceClassification from MinzaKhan +author: John Snow Labs +name: toxic +date: 2024-09-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxic` is a English model originally trained by MinzaKhan. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxic_en_5.5.0_3.0_1727376676693.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxic_en_5.5.0_3.0_1727376676693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = DistilBertForSequenceClassification.pretrained("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 = DistilBertForSequenceClassification.pretrained("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:|toxic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +References + +https://huggingface.co/MinzaKhan/toxic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-toxic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-toxic_pipeline_en.md new file mode 100644 index 00000000000000..c2adcd3b9cc817 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-toxic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English toxic_pipeline pipeline BertForSequenceClassification from MarianaMoon +author: John Snow Labs +name: toxic_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`toxic_pipeline` is a English model originally trained by MarianaMoon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/toxic_pipeline_en_5.5.0_3.0_1727376697751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/toxic_pipeline_en_5.5.0_3.0_1727376697751.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("toxic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("toxic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|toxic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MarianaMoon/Toxic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tps_sentimental_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-26-tps_sentimental_analysis_en.md new file mode 100644 index 00000000000000..6b5b3c5bfc8f32 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tps_sentimental_analysis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tps_sentimental_analysis BertForSequenceClassification from Startup-Exchange +author: John Snow Labs +name: tps_sentimental_analysis +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tps_sentimental_analysis` is a English model originally trained by Startup-Exchange. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tps_sentimental_analysis_en_5.5.0_3.0_1727378094546.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tps_sentimental_analysis_en_5.5.0_3.0_1727378094546.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("tps_sentimental_analysis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tps_sentimental_analysis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tps_sentimental_analysis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Startup-Exchange/tps_sentimental_analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-trac2020_eng_a_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-26-trac2020_eng_a_bert_base_uncased_en.md new file mode 100644 index 00000000000000..2b1a8ee38019e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-trac2020_eng_a_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English trac2020_eng_a_bert_base_uncased BertForSequenceClassification from socialmediaie +author: John Snow Labs +name: trac2020_eng_a_bert_base_uncased +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trac2020_eng_a_bert_base_uncased` is a English model originally trained by socialmediaie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trac2020_eng_a_bert_base_uncased_en_5.5.0_3.0_1727311545787.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trac2020_eng_a_bert_base_uncased_en_5.5.0_3.0_1727311545787.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("trac2020_eng_a_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("trac2020_eng_a_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|trac2020_eng_a_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/socialmediaie/TRAC2020_ENG_A_bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-trac2020_eng_b_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-trac2020_eng_b_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..543e8c9a5808f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-trac2020_eng_b_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English trac2020_eng_b_bert_base_uncased_pipeline pipeline BertForSequenceClassification from socialmediaie +author: John Snow Labs +name: trac2020_eng_b_bert_base_uncased_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trac2020_eng_b_bert_base_uncased_pipeline` is a English model originally trained by socialmediaie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trac2020_eng_b_bert_base_uncased_pipeline_en_5.5.0_3.0_1727339901567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trac2020_eng_b_bert_base_uncased_pipeline_en_5.5.0_3.0_1727339901567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("trac2020_eng_b_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("trac2020_eng_b_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|trac2020_eng_b_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/socialmediaie/TRAC2020_ENG_B_bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tupi_bert_base_portuguese_cased_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-26-tupi_bert_base_portuguese_cased_pipeline_pt.md new file mode 100644 index 00000000000000..9e7ee702e6b86a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tupi_bert_base_portuguese_cased_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese tupi_bert_base_portuguese_cased_pipeline pipeline BertForSequenceClassification from FpOliveira +author: John Snow Labs +name: tupi_bert_base_portuguese_cased_pipeline +date: 2024-09-26 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tupi_bert_base_portuguese_cased_pipeline` is a Portuguese model originally trained by FpOliveira. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tupi_bert_base_portuguese_cased_pipeline_pt_5.5.0_3.0_1727378646598.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tupi_bert_base_portuguese_cased_pipeline_pt_5.5.0_3.0_1727378646598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tupi_bert_base_portuguese_cased_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tupi_bert_base_portuguese_cased_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tupi_bert_base_portuguese_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|408.2 MB| + +## References + +https://huggingface.co/FpOliveira/tupi-bert-base-portuguese-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-tupi_bert_base_portuguese_cased_pt.md b/docs/_posts/ahmedlone127/2024-09-26-tupi_bert_base_portuguese_cased_pt.md new file mode 100644 index 00000000000000..c4c2efbe0b7189 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-tupi_bert_base_portuguese_cased_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese tupi_bert_base_portuguese_cased BertForSequenceClassification from FpOliveira +author: John Snow Labs +name: tupi_bert_base_portuguese_cased +date: 2024-09-26 +tags: [pt, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tupi_bert_base_portuguese_cased` is a Portuguese model originally trained by FpOliveira. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tupi_bert_base_portuguese_cased_pt_5.5.0_3.0_1727378624751.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tupi_bert_base_portuguese_cased_pt_5.5.0_3.0_1727378624751.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("tupi_bert_base_portuguese_cased","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tupi_bert_base_portuguese_cased", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tupi_bert_base_portuguese_cased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.2 MB| + +## References + +https://huggingface.co/FpOliveira/tupi-bert-base-portuguese-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-turkish_base_bert_uncased_offenseval2020_turkish_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-26-turkish_base_bert_uncased_offenseval2020_turkish_pipeline_tr.md new file mode 100644 index 00000000000000..07c766dc14553f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-turkish_base_bert_uncased_offenseval2020_turkish_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish turkish_base_bert_uncased_offenseval2020_turkish_pipeline pipeline BertForSequenceClassification from atasoglu +author: John Snow Labs +name: turkish_base_bert_uncased_offenseval2020_turkish_pipeline +date: 2024-09-26 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_base_bert_uncased_offenseval2020_turkish_pipeline` is a Turkish model originally trained by atasoglu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_base_bert_uncased_offenseval2020_turkish_pipeline_tr_5.5.0_3.0_1727386284253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_base_bert_uncased_offenseval2020_turkish_pipeline_tr_5.5.0_3.0_1727386284253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("turkish_base_bert_uncased_offenseval2020_turkish_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("turkish_base_bert_uncased_offenseval2020_turkish_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_base_bert_uncased_offenseval2020_turkish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|415.3 MB| + +## References + +https://huggingface.co/atasoglu/turkish-base-bert-uncased-offenseval2020_tr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-turkish_org_classifier_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-26-turkish_org_classifier_pipeline_tr.md new file mode 100644 index 00000000000000..acb686f427cdd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-turkish_org_classifier_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish turkish_org_classifier_pipeline pipeline BertForSequenceClassification from atsizelti +author: John Snow Labs +name: turkish_org_classifier_pipeline +date: 2024-09-26 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_org_classifier_pipeline` is a Turkish model originally trained by atsizelti. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_org_classifier_pipeline_tr_5.5.0_3.0_1727377259565.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_org_classifier_pipeline_tr_5.5.0_3.0_1727377259565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("turkish_org_classifier_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("turkish_org_classifier_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_org_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|414.7 MB| + +## References + +https://huggingface.co/atsizelti/turkish_org_classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-turkish_org_classifier_tr.md b/docs/_posts/ahmedlone127/2024-09-26-turkish_org_classifier_tr.md new file mode 100644 index 00000000000000..58fe7c250bd332 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-turkish_org_classifier_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish turkish_org_classifier BertForSequenceClassification from atsizelti +author: John Snow Labs +name: turkish_org_classifier +date: 2024-09-26 +tags: [tr, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkish_org_classifier` is a Turkish model originally trained by atsizelti. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkish_org_classifier_tr_5.5.0_3.0_1727377237020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkish_org_classifier_tr_5.5.0_3.0_1727377237020.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("turkish_org_classifier","tr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("turkish_org_classifier", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkish_org_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|414.7 MB| + +## References + +https://huggingface.co/atsizelti/turkish_org_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-turkqp_en.md b/docs/_posts/ahmedlone127/2024-09-26-turkqp_en.md new file mode 100644 index 00000000000000..d8bb7a836e765f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-turkqp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English turkqp BertForSequenceClassification from savasy +author: John Snow Labs +name: turkqp +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkqp` is a English model originally trained by savasy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkqp_en_5.5.0_3.0_1727366993566.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkqp_en_5.5.0_3.0_1727366993566.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("turkqp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("turkqp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkqp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.5 MB| + +## References + +https://huggingface.co/savasy/TurkQP \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-turkqp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-turkqp_pipeline_en.md new file mode 100644 index 00000000000000..589b3dbf996743 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-turkqp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English turkqp_pipeline pipeline BertForSequenceClassification from savasy +author: John Snow Labs +name: turkqp_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkqp_pipeline` is a English model originally trained by savasy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkqp_pipeline_en_5.5.0_3.0_1727367015109.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkqp_pipeline_en_5.5.0_3.0_1727367015109.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("turkqp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("turkqp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkqp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.5 MB| + +## References + +https://huggingface.co/savasy/TurkQP + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-unsup_simcse_minilm_l6_en.md b/docs/_posts/ahmedlone127/2024-09-26-unsup_simcse_minilm_l6_en.md new file mode 100644 index 00000000000000..7a30e5a6ad48f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-unsup_simcse_minilm_l6_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English unsup_simcse_minilm_l6 BertForSequenceClassification from kevinng77 +author: John Snow Labs +name: unsup_simcse_minilm_l6 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unsup_simcse_minilm_l6` is a English model originally trained by kevinng77. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unsup_simcse_minilm_l6_en_5.5.0_3.0_1727390984176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unsup_simcse_minilm_l6_en_5.5.0_3.0_1727390984176.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("unsup_simcse_minilm_l6","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("unsup_simcse_minilm_l6", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unsup_simcse_minilm_l6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|84.5 MB| + +## References + +https://huggingface.co/kevinng77/unsup_simcse_MiniLM_L6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-unsup_simcse_minilm_l6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-unsup_simcse_minilm_l6_pipeline_en.md new file mode 100644 index 00000000000000..c3f969102e23b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-unsup_simcse_minilm_l6_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English unsup_simcse_minilm_l6_pipeline pipeline BertForSequenceClassification from kevinng77 +author: John Snow Labs +name: unsup_simcse_minilm_l6_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unsup_simcse_minilm_l6_pipeline` is a English model originally trained by kevinng77. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unsup_simcse_minilm_l6_pipeline_en_5.5.0_3.0_1727390989050.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unsup_simcse_minilm_l6_pipeline_en_5.5.0_3.0_1727390989050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("unsup_simcse_minilm_l6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("unsup_simcse_minilm_l6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unsup_simcse_minilm_l6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|84.5 MB| + +## References + +https://huggingface.co/kevinng77/unsup_simcse_MiniLM_L6 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-vaccinchatsentenceclassifierdutch_frombertje_en.md b/docs/_posts/ahmedlone127/2024-09-26-vaccinchatsentenceclassifierdutch_frombertje_en.md new file mode 100644 index 00000000000000..ea705e493ecfbd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-vaccinchatsentenceclassifierdutch_frombertje_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English vaccinchatsentenceclassifierdutch_frombertje BertForSequenceClassification from Jeska +author: John Snow Labs +name: vaccinchatsentenceclassifierdutch_frombertje +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vaccinchatsentenceclassifierdutch_frombertje` is a English model originally trained by Jeska. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vaccinchatsentenceclassifierdutch_frombertje_en_5.5.0_3.0_1727379617652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vaccinchatsentenceclassifierdutch_frombertje_en_5.5.0_3.0_1727379617652.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("vaccinchatsentenceclassifierdutch_frombertje","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("vaccinchatsentenceclassifierdutch_frombertje", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vaccinchatsentenceclassifierdutch_frombertje| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Jeska/VaccinChatSentenceClassifierDutch_fromBERTje \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-valueeval24_bert_baseline_english_2024_02_15_en.md b/docs/_posts/ahmedlone127/2024-09-26-valueeval24_bert_baseline_english_2024_02_15_en.md new file mode 100644 index 00000000000000..34247193d0ed8b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-valueeval24_bert_baseline_english_2024_02_15_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English valueeval24_bert_baseline_english_2024_02_15 BertForSequenceClassification from JohannesKiesel +author: John Snow Labs +name: valueeval24_bert_baseline_english_2024_02_15 +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`valueeval24_bert_baseline_english_2024_02_15` is a English model originally trained by JohannesKiesel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/valueeval24_bert_baseline_english_2024_02_15_en_5.5.0_3.0_1727379160796.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/valueeval24_bert_baseline_english_2024_02_15_en_5.5.0_3.0_1727379160796.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("valueeval24_bert_baseline_english_2024_02_15","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("valueeval24_bert_baseline_english_2024_02_15", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|valueeval24_bert_baseline_english_2024_02_15| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/JohannesKiesel/valueeval24-bert-baseline-en-2024-02-15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-vetbertdx_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-vetbertdx_pipeline_en.md new file mode 100644 index 00000000000000..cdba8652471d05 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-vetbertdx_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English vetbertdx_pipeline pipeline BertForSequenceClassification from havocy28 +author: John Snow Labs +name: vetbertdx_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vetbertdx_pipeline` is a English model originally trained by havocy28. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vetbertdx_pipeline_en_5.5.0_3.0_1727335019206.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vetbertdx_pipeline_en_5.5.0_3.0_1727335019206.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("vetbertdx_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("vetbertdx_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vetbertdx_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.2 MB| + +## References + +https://huggingface.co/havocy28/VetBERTDx + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-violence_hate_bert_german_en.md b/docs/_posts/ahmedlone127/2024-09-26-violence_hate_bert_german_en.md new file mode 100644 index 00000000000000..6ea7441f39c5b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-violence_hate_bert_german_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English violence_hate_bert_german BertForSequenceClassification from catalpa-cl +author: John Snow Labs +name: violence_hate_bert_german +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`violence_hate_bert_german` is a English model originally trained by catalpa-cl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/violence_hate_bert_german_en_5.5.0_3.0_1727365435170.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/violence_hate_bert_german_en_5.5.0_3.0_1727365435170.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("violence_hate_bert_german","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("violence_hate_bert_german", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|violence_hate_bert_german| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/catalpa-cl/violence-hate-bert-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-violence_hate_bert_german_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-violence_hate_bert_german_pipeline_en.md new file mode 100644 index 00000000000000..01f3a8ce57548d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-violence_hate_bert_german_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English violence_hate_bert_german_pipeline pipeline BertForSequenceClassification from catalpa-cl +author: John Snow Labs +name: violence_hate_bert_german_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`violence_hate_bert_german_pipeline` is a English model originally trained by catalpa-cl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/violence_hate_bert_german_pipeline_en_5.5.0_3.0_1727365455606.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/violence_hate_bert_german_pipeline_en_5.5.0_3.0_1727365455606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("violence_hate_bert_german_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("violence_hate_bert_german_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|violence_hate_bert_german_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/catalpa-cl/violence-hate-bert-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-waste_classification_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-waste_classification_2_pipeline_en.md new file mode 100644 index 00000000000000..3d786d757822dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-waste_classification_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English waste_classification_2_pipeline pipeline BertForSequenceClassification from XYZ123XYZ +author: John Snow Labs +name: waste_classification_2_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`waste_classification_2_pipeline` is a English model originally trained by XYZ123XYZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/waste_classification_2_pipeline_en_5.5.0_3.0_1727374906860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/waste_classification_2_pipeline_en_5.5.0_3.0_1727374906860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("waste_classification_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("waste_classification_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|waste_classification_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/XYZ123XYZ/waste-classification-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-zeroshotwiki_en.md b/docs/_posts/ahmedlone127/2024-09-26-zeroshotwiki_en.md new file mode 100644 index 00000000000000..65cb218a72a166 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-zeroshotwiki_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English zeroshotwiki BertForSequenceClassification from CogComp +author: John Snow Labs +name: zeroshotwiki +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zeroshotwiki` is a English model originally trained by CogComp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zeroshotwiki_en_5.5.0_3.0_1727378340397.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zeroshotwiki_en_5.5.0_3.0_1727378340397.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("zeroshotwiki","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("zeroshotwiki", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|zeroshotwiki| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/CogComp/ZeroShotWiki \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-zeroshotwiki_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-26-zeroshotwiki_pipeline_en.md new file mode 100644 index 00000000000000..8064548b6309ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-zeroshotwiki_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English zeroshotwiki_pipeline pipeline BertForSequenceClassification from CogComp +author: John Snow Labs +name: zeroshotwiki_pipeline +date: 2024-09-26 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zeroshotwiki_pipeline` is a English model originally trained by CogComp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zeroshotwiki_pipeline_en_5.5.0_3.0_1727378363085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zeroshotwiki_pipeline_en_5.5.0_3.0_1727378363085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("zeroshotwiki_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("zeroshotwiki_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|zeroshotwiki_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/CogComp/ZeroShotWiki + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-26-zipbasemodel_en.md b/docs/_posts/ahmedlone127/2024-09-26-zipbasemodel_en.md new file mode 100644 index 00000000000000..0d148fcbd6548f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-26-zipbasemodel_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English zipbasemodel BertForSequenceClassification from privacy-tech-lab +author: John Snow Labs +name: zipbasemodel +date: 2024-09-26 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`zipbasemodel` is a English model originally trained by privacy-tech-lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zipbasemodel_en_5.5.0_3.0_1727384499877.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zipbasemodel_en_5.5.0_3.0_1727384499877.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("zipbasemodel","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("zipbasemodel", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|zipbasemodel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/privacy-tech-lab/ZipBaseModel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-aann_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-aann_detector_pipeline_en.md new file mode 100644 index 00000000000000..43afaa161b1028 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-aann_detector_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English aann_detector_pipeline pipeline BertForSequenceClassification from kanishka +author: John Snow Labs +name: aann_detector_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aann_detector_pipeline` is a English model originally trained by kanishka. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aann_detector_pipeline_en_5.5.0_3.0_1727418813682.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aann_detector_pipeline_en_5.5.0_3.0_1727418813682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("aann_detector_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("aann_detector_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aann_detector_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kanishka/aann-detector + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-adversarial_trainer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-adversarial_trainer_pipeline_en.md new file mode 100644 index 00000000000000..27f9f6f64a4c4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-adversarial_trainer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English adversarial_trainer_pipeline pipeline BertForSequenceClassification from michalzajac +author: John Snow Labs +name: adversarial_trainer_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adversarial_trainer_pipeline` is a English model originally trained by michalzajac. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adversarial_trainer_pipeline_en_5.5.0_3.0_1727419642875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adversarial_trainer_pipeline_en_5.5.0_3.0_1727419642875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("adversarial_trainer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("adversarial_trainer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|adversarial_trainer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/michalzajac/adversarial_trainer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-ag_news_4800_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-27-ag_news_4800_bert_base_uncased_en.md new file mode 100644 index 00000000000000..6993e17d725c72 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-ag_news_4800_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ag_news_4800_bert_base_uncased BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: ag_news_4800_bert_base_uncased +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_4800_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_4800_bert_base_uncased_en_5.5.0_3.0_1727400326939.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ag_news_4800_bert_base_uncased_en_5.5.0_3.0_1727400326939.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("ag_news_4800_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ag_news_4800_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ag_news_4800_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/ag-news-4800-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-ai_generated_text_detection_pair_zh.md b/docs/_posts/ahmedlone127/2024-09-27-ai_generated_text_detection_pair_zh.md new file mode 100644 index 00000000000000..3ae767f08af0a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-ai_generated_text_detection_pair_zh.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Chinese ai_generated_text_detection_pair BertForSequenceClassification from Juner +author: John Snow Labs +name: ai_generated_text_detection_pair +date: 2024-09-27 +tags: [zh, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: zh +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ai_generated_text_detection_pair` is a Chinese model originally trained by Juner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ai_generated_text_detection_pair_zh_5.5.0_3.0_1727405235051.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ai_generated_text_detection_pair_zh_5.5.0_3.0_1727405235051.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("ai_generated_text_detection_pair","zh") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ai_generated_text_detection_pair", "zh") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ai_generated_text_detection_pair| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|zh| +|Size:|383.2 MB| + +## References + +https://huggingface.co/Juner/AI-generated-text-detection-pair \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-albert_base_chinese_finetuned_qqp_tm_5x_en.md b/docs/_posts/ahmedlone127/2024-09-27-albert_base_chinese_finetuned_qqp_tm_5x_en.md new file mode 100644 index 00000000000000..d3850d2769103e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-albert_base_chinese_finetuned_qqp_tm_5x_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_base_chinese_finetuned_qqp_tm_5x BertForSequenceClassification from r10521708 +author: John Snow Labs +name: albert_base_chinese_finetuned_qqp_tm_5x +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_base_chinese_finetuned_qqp_tm_5x` is a English model originally trained by r10521708. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_base_chinese_finetuned_qqp_tm_5x_en_5.5.0_3.0_1727400432818.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_base_chinese_finetuned_qqp_tm_5x_en_5.5.0_3.0_1727400432818.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("albert_base_chinese_finetuned_qqp_tm_5x","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("albert_base_chinese_finetuned_qqp_tm_5x", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_base_chinese_finetuned_qqp_tm_5x| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|39.8 MB| + +## References + +https://huggingface.co/r10521708/albert-base-chinese-finetuned-qqp-TM-5x \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-albert_chinese_base_text_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-albert_chinese_base_text_classification_en.md new file mode 100644 index 00000000000000..ee06130a99e692 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-albert_chinese_base_text_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_chinese_base_text_classification BertForSequenceClassification from CeroShrijver +author: John Snow Labs +name: albert_chinese_base_text_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_chinese_base_text_classification` is a English model originally trained by CeroShrijver. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_chinese_base_text_classification_en_5.5.0_3.0_1727399740127.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_chinese_base_text_classification_en_5.5.0_3.0_1727399740127.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("albert_chinese_base_text_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("albert_chinese_base_text_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_chinese_base_text_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|39.8 MB| + +## References + +https://huggingface.co/CeroShrijver/albert_chinese_base-text-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-all_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-all_classification_en.md new file mode 100644 index 00000000000000..2caedb302b648a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-all_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English all_classification BertForSequenceClassification from bharadwajkg +author: John Snow Labs +name: all_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_classification` is a English model originally trained by bharadwajkg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_classification_en_5.5.0_3.0_1727406683712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_classification_en_5.5.0_3.0_1727406683712.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("all_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("all_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/bharadwajkg/all_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-all_mini_finetuned_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-27-all_mini_finetuned_imdb_en.md new file mode 100644 index 00000000000000..b5667e4f7739a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-all_mini_finetuned_imdb_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English all_mini_finetuned_imdb BertForSequenceClassification from DBretsko +author: John Snow Labs +name: all_mini_finetuned_imdb +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mini_finetuned_imdb` is a English model originally trained by DBretsko. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mini_finetuned_imdb_en_5.5.0_3.0_1727409291205.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mini_finetuned_imdb_en_5.5.0_3.0_1727409291205.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("all_mini_finetuned_imdb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("all_mini_finetuned_imdb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mini_finetuned_imdb| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|84.6 MB| + +## References + +https://huggingface.co/DBretsko/all-Mini-finetuned-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-amazon_review_es.md b/docs/_posts/ahmedlone127/2024-09-27-amazon_review_es.md new file mode 100644 index 00000000000000..ceac1b24755828 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-amazon_review_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish amazon_review BertForSequenceClassification from luisu0124 +author: John Snow Labs +name: amazon_review +date: 2024-09-27 +tags: [es, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amazon_review` is a Castilian, Spanish model originally trained by luisu0124. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amazon_review_es_5.5.0_3.0_1727403309546.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amazon_review_es_5.5.0_3.0_1727403309546.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("amazon_review","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("amazon_review", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|amazon_review| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|16.7 MB| + +## References + +https://huggingface.co/luisu0124/Amazon_review \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-amazon_review_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-27-amazon_review_pipeline_es.md new file mode 100644 index 00000000000000..8d583ac8b28ac2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-amazon_review_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish amazon_review_pipeline pipeline BertForSequenceClassification from luisu0124 +author: John Snow Labs +name: amazon_review_pipeline +date: 2024-09-27 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amazon_review_pipeline` is a Castilian, Spanish model originally trained by luisu0124. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amazon_review_pipeline_es_5.5.0_3.0_1727403310870.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amazon_review_pipeline_es_5.5.0_3.0_1727403310870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("amazon_review_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("amazon_review_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|amazon_review_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|16.8 MB| + +## References + +https://huggingface.co/luisu0124/Amazon_review + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-amazon_reviews_finetuning_sentiment_model_3000_samples_en.md b/docs/_posts/ahmedlone127/2024-09-27-amazon_reviews_finetuning_sentiment_model_3000_samples_en.md new file mode 100644 index 00000000000000..c522be2f3e4f1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-amazon_reviews_finetuning_sentiment_model_3000_samples_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English amazon_reviews_finetuning_sentiment_model_3000_samples BertForSequenceClassification from santiviquez +author: John Snow Labs +name: amazon_reviews_finetuning_sentiment_model_3000_samples +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amazon_reviews_finetuning_sentiment_model_3000_samples` is a English model originally trained by santiviquez. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amazon_reviews_finetuning_sentiment_model_3000_samples_en_5.5.0_3.0_1727413784045.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amazon_reviews_finetuning_sentiment_model_3000_samples_en_5.5.0_3.0_1727413784045.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("amazon_reviews_finetuning_sentiment_model_3000_samples","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("amazon_reviews_finetuning_sentiment_model_3000_samples", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|amazon_reviews_finetuning_sentiment_model_3000_samples| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.8 MB| + +## References + +https://huggingface.co/santiviquez/amazon_reviews_finetuning-sentiment-model-3000-samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline_en.md new file mode 100644 index 00000000000000..98b154e346e759 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline pipeline BertForSequenceClassification from santiviquez +author: John Snow Labs +name: amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline` is a English model originally trained by santiviquez. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline_en_5.5.0_3.0_1727413823269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline_en_5.5.0_3.0_1727413823269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|amazon_reviews_finetuning_sentiment_model_3000_samples_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|627.8 MB| + +## References + +https://huggingface.co/santiviquez/amazon_reviews_finetuning-sentiment-model-3000-samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-arabic_bank77_intent_classification_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-27-arabic_bank77_intent_classification_pipeline_ar.md new file mode 100644 index 00000000000000..aac553b184e80a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-arabic_bank77_intent_classification_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic arabic_bank77_intent_classification_pipeline pipeline BertForSequenceClassification from bassemessam +author: John Snow Labs +name: arabic_bank77_intent_classification_pipeline +date: 2024-09-27 +tags: [ar, open_source, pipeline, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_bank77_intent_classification_pipeline` is a Arabic model originally trained by bassemessam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabic_bank77_intent_classification_pipeline_ar_5.5.0_3.0_1727414093863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_bank77_intent_classification_pipeline_ar_5.5.0_3.0_1727414093863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("arabic_bank77_intent_classification_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("arabic_bank77_intent_classification_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabic_bank77_intent_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|507.5 MB| + +## References + +https://huggingface.co/bassemessam/Arabic-bank77-intent-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-arabic_tweets_spam_oriya_ham_en.md b/docs/_posts/ahmedlone127/2024-09-27-arabic_tweets_spam_oriya_ham_en.md new file mode 100644 index 00000000000000..91a100e76a8eea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-arabic_tweets_spam_oriya_ham_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English arabic_tweets_spam_oriya_ham BertForSequenceClassification from Abdelkareem +author: John Snow Labs +name: arabic_tweets_spam_oriya_ham +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`arabic_tweets_spam_oriya_ham` is a English model originally trained by Abdelkareem. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/arabic_tweets_spam_oriya_ham_en_5.5.0_3.0_1727405061899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/arabic_tweets_spam_oriya_ham_en_5.5.0_3.0_1727405061899.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("arabic_tweets_spam_oriya_ham","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("arabic_tweets_spam_oriya_ham", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|arabic_tweets_spam_oriya_ham| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/Abdelkareem/arabic_tweets_spam_or_ham \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-autotrain_4usrt_85kzb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-autotrain_4usrt_85kzb_pipeline_en.md new file mode 100644 index 00000000000000..3ad0807e3a04e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-autotrain_4usrt_85kzb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_4usrt_85kzb_pipeline pipeline BertForSequenceClassification from airabbitX +author: John Snow Labs +name: autotrain_4usrt_85kzb_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_4usrt_85kzb_pipeline` is a English model originally trained by airabbitX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_4usrt_85kzb_pipeline_en_5.5.0_3.0_1727404635163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_4usrt_85kzb_pipeline_en_5.5.0_3.0_1727404635163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_4usrt_85kzb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_4usrt_85kzb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_4usrt_85kzb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/airabbitX/autotrain-4usrt-85kzb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-autotrain_bertbase_imdb_1275748791_en.md b/docs/_posts/ahmedlone127/2024-09-27-autotrain_bertbase_imdb_1275748791_en.md new file mode 100644 index 00000000000000..f4709abe40a06f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-autotrain_bertbase_imdb_1275748791_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autotrain_bertbase_imdb_1275748791 BertForSequenceClassification from sasha +author: John Snow Labs +name: autotrain_bertbase_imdb_1275748791 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_bertbase_imdb_1275748791` is a English model originally trained by sasha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748791_en_5.5.0_3.0_1727405958299.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748791_en_5.5.0_3.0_1727405958299.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("autotrain_bertbase_imdb_1275748791","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_bertbase_imdb_1275748791", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_bertbase_imdb_1275748791| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasha/autotrain-BERTBase-imdb-1275748791 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-autotrain_bertbase_imdb_1275748791_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-autotrain_bertbase_imdb_1275748791_pipeline_en.md new file mode 100644 index 00000000000000..27b79484d95e35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-autotrain_bertbase_imdb_1275748791_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_bertbase_imdb_1275748791_pipeline pipeline BertForSequenceClassification from sasha +author: John Snow Labs +name: autotrain_bertbase_imdb_1275748791_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_bertbase_imdb_1275748791_pipeline` is a English model originally trained by sasha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748791_pipeline_en_5.5.0_3.0_1727405980592.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_bertbase_imdb_1275748791_pipeline_en_5.5.0_3.0_1727405980592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_bertbase_imdb_1275748791_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_bertbase_imdb_1275748791_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_bertbase_imdb_1275748791_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasha/autotrain-BERTBase-imdb-1275748791 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-autotrain_osb1a_e71jf_en.md b/docs/_posts/ahmedlone127/2024-09-27-autotrain_osb1a_e71jf_en.md new file mode 100644 index 00000000000000..f41700197c7278 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-autotrain_osb1a_e71jf_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autotrain_osb1a_e71jf BertForSequenceClassification from deveshk12 +author: John Snow Labs +name: autotrain_osb1a_e71jf +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_osb1a_e71jf` is a English model originally trained by deveshk12. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_osb1a_e71jf_en_5.5.0_3.0_1727415023720.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_osb1a_e71jf_en_5.5.0_3.0_1727415023720.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("autotrain_osb1a_e71jf","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_osb1a_e71jf", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_osb1a_e71jf| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/deveshk12/autotrain-osb1a-e71jf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-autotrain_osb1a_e71jf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-autotrain_osb1a_e71jf_pipeline_en.md new file mode 100644 index 00000000000000..e1e10583b1a296 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-autotrain_osb1a_e71jf_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_osb1a_e71jf_pipeline pipeline BertForSequenceClassification from deveshk12 +author: John Snow Labs +name: autotrain_osb1a_e71jf_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_osb1a_e71jf_pipeline` is a English model originally trained by deveshk12. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_osb1a_e71jf_pipeline_en_5.5.0_3.0_1727415044329.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_osb1a_e71jf_pipeline_en_5.5.0_3.0_1727415044329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_osb1a_e71jf_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_osb1a_e71jf_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_osb1a_e71jf_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/deveshk12/autotrain-osb1a-e71jf + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_en.md b/docs/_posts/ahmedlone127/2024-09-27-belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_en.md new file mode 100644 index 00000000000000..f112ffd20cbe6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34 BertForSequenceClassification from maxaalexeeva +author: John Snow Labs +name: belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34` is a English model originally trained by maxaalexeeva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_en_5.5.0_3.0_1727406397510.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_en_5.5.0_3.0_1727406397510.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("belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/maxaalexeeva/belief-classifier_mturk_unmarked-trigger_bert-base-cased_2023-4-26-0-34 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline_en.md new file mode 100644 index 00000000000000..1ec69ba20512e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline pipeline BertForSequenceClassification from maxaalexeeva +author: John Snow Labs +name: belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline` is a English model originally trained by maxaalexeeva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline_en_5.5.0_3.0_1727406417775.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline_en_5.5.0_3.0_1727406417775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|belief_classifier_mturk_unmarked_trigger_bert_base_cased_2023_4_26_0_34_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/maxaalexeeva/belief-classifier_mturk_unmarked-trigger_bert-base-cased_2023-4-26-0-34 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline_en.md new file mode 100644 index 00000000000000..a9e3d73f2e880e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline pipeline BertForSequenceClassification from MatMulMan +author: John Snow Labs +name: bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline` is a English model originally trained by MatMulMan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline_en_5.5.0_3.0_1727413619374.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline_en_5.5.0_3.0_1727413619374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_catalan_tafseer_pairs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/MatMulMan/bert-base-arabic-camelbert-ca-tafseer-pairs + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_abusarim_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_abusarim_en.md new file mode 100644 index 00000000000000..f5fddf47a2ec45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_abusarim_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pt2_abusarim BertForSequenceClassification from abusarim +author: John Snow Labs +name: bert_base_banking77_pt2_abusarim +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_abusarim` is a English model originally trained by abusarim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_abusarim_en_5.5.0_3.0_1727408642858.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_abusarim_en_5.5.0_3.0_1727408642858.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_base_banking77_pt2_abusarim","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_abusarim", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_abusarim| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/abusarim/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_abusarim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_abusarim_pipeline_en.md new file mode 100644 index 00000000000000..3d45a29db377d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_abusarim_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_abusarim_pipeline pipeline BertForSequenceClassification from abusarim +author: John Snow Labs +name: bert_base_banking77_pt2_abusarim_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_abusarim_pipeline` is a English model originally trained by abusarim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_abusarim_pipeline_en_5.5.0_3.0_1727408666572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_abusarim_pipeline_en_5.5.0_3.0_1727408666572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_abusarim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_abusarim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_abusarim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/abusarim/bert-base-banking77-pt2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_donmakar_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_donmakar_en.md new file mode 100644 index 00000000000000..a88cf6d149ac75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_donmakar_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pt2_donmakar BertForSequenceClassification from DonMakar +author: John Snow Labs +name: bert_base_banking77_pt2_donmakar +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_donmakar` is a English model originally trained by DonMakar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_donmakar_en_5.5.0_3.0_1727418924404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_donmakar_en_5.5.0_3.0_1727418924404.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_base_banking77_pt2_donmakar","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_donmakar", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_donmakar| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DonMakar/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_eoeelocr_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_eoeelocr_en.md new file mode 100644 index 00000000000000..1a5043427e2250 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_eoeelocr_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pt2_eoeelocr BertForSequenceClassification from eoeelocr +author: John Snow Labs +name: bert_base_banking77_pt2_eoeelocr +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_eoeelocr` is a English model originally trained by eoeelocr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_eoeelocr_en_5.5.0_3.0_1727397318344.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_eoeelocr_en_5.5.0_3.0_1727397318344.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_base_banking77_pt2_eoeelocr","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_eoeelocr", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_eoeelocr| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/eoeelocr/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_eoeelocr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_eoeelocr_pipeline_en.md new file mode 100644 index 00000000000000..6c96bb75ea04d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_eoeelocr_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_eoeelocr_pipeline pipeline BertForSequenceClassification from eoeelocr +author: John Snow Labs +name: bert_base_banking77_pt2_eoeelocr_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_eoeelocr_pipeline` is a English model originally trained by eoeelocr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_eoeelocr_pipeline_en_5.5.0_3.0_1727397339191.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_eoeelocr_pipeline_en_5.5.0_3.0_1727397339191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_eoeelocr_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_eoeelocr_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_eoeelocr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/eoeelocr/bert-base-banking77-pt2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_rob_braswell_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_rob_braswell_pipeline_en.md new file mode 100644 index 00000000000000..ebed506851569d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_rob_braswell_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_rob_braswell_pipeline pipeline BertForSequenceClassification from rob-braswell +author: John Snow Labs +name: bert_base_banking77_pt2_rob_braswell_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_rob_braswell_pipeline` is a English model originally trained by rob-braswell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_rob_braswell_pipeline_en_5.5.0_3.0_1727418493713.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_rob_braswell_pipeline_en_5.5.0_3.0_1727418493713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_rob_braswell_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_rob_braswell_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_rob_braswell_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/rob-braswell/bert-base-banking77-pt2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_szilard_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_szilard_pipeline_en.md new file mode 100644 index 00000000000000..87d53f54bdd018 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_szilard_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_szilard_pipeline pipeline BertForSequenceClassification from szilard +author: John Snow Labs +name: bert_base_banking77_pt2_szilard_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_szilard_pipeline` is a English model originally trained by szilard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_szilard_pipeline_en_5.5.0_3.0_1727418075311.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_szilard_pipeline_en_5.5.0_3.0_1727418075311.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_szilard_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_szilard_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_szilard_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/szilard/bert-base-banking77-pt2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_tanlda_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_tanlda_en.md new file mode 100644 index 00000000000000..f5943e3a4aeb2f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_tanlda_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_banking77_pt2_tanlda BertForSequenceClassification from tanlda +author: John Snow Labs +name: bert_base_banking77_pt2_tanlda +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_tanlda` is a English model originally trained by tanlda. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_tanlda_en_5.5.0_3.0_1727407585168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_tanlda_en_5.5.0_3.0_1727407585168.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_base_banking77_pt2_tanlda","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_tanlda", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_tanlda| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/tanlda/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_tanlda_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_tanlda_pipeline_en.md new file mode 100644 index 00000000000000..8f35edbdaabe4c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_banking77_pt2_tanlda_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_banking77_pt2_tanlda_pipeline pipeline BertForSequenceClassification from tanlda +author: John Snow Labs +name: bert_base_banking77_pt2_tanlda_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_tanlda_pipeline` is a English model originally trained by tanlda. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_tanlda_pipeline_en_5.5.0_3.0_1727407606247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_tanlda_pipeline_en_5.5.0_3.0_1727407606247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_banking77_pt2_tanlda_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_banking77_pt2_tanlda_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_tanlda_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/tanlda/bert-base-banking77-pt2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_fine_tuned_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_fine_tuned_en.md new file mode 100644 index 00000000000000..60a9400573e5ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_fine_tuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_fine_tuned BertForSequenceClassification from yousseftarhri +author: John Snow Labs +name: bert_base_cased_fine_tuned +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_fine_tuned` is a English model originally trained by yousseftarhri. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_fine_tuned_en_5.5.0_3.0_1727411871920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_fine_tuned_en_5.5.0_3.0_1727411871920.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_base_cased_fine_tuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_fine_tuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_fine_tuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/yousseftarhri/bert-base-cased_fine_tuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_mrpc_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_mrpc_en.md new file mode 100644 index 00000000000000..04da9811a99401 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_mrpc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_finetuned_mrpc BertEmbeddings from huggingface +author: John Snow Labs +name: bert_base_cased_finetuned_mrpc +date: 2024-09-27 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_mrpc` is a English model originally trained by huggingface. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_mrpc_en_5.5.0_3.0_1727411684819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_mrpc_en_5.5.0_3.0_1727411684819.zip){:.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 =BertEmbeddings.pretrained("bert_base_cased_finetuned_mrpc","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 = BertEmbeddings + .pretrained("bert_base_cased_finetuned_mrpc", "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:|bert_base_cased_finetuned_mrpc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +References + +References + +https://huggingface.co/bert-base-cased-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_open_ended_questions_english_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_open_ended_questions_english_en.md new file mode 100644 index 00000000000000..92329085d0e8f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_open_ended_questions_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_finetuned_open_ended_questions_english BertForSequenceClassification from arl949 +author: John Snow Labs +name: bert_base_cased_finetuned_open_ended_questions_english +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_open_ended_questions_english` is a English model originally trained by arl949. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_open_ended_questions_english_en_5.5.0_3.0_1727401877052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_open_ended_questions_english_en_5.5.0_3.0_1727401877052.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_base_cased_finetuned_open_ended_questions_english","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetuned_open_ended_questions_english", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_open_ended_questions_english| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/arl949/bert-base-cased-finetuned-open-ended-questions-english \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_qqp_w05230505_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_qqp_w05230505_en.md new file mode 100644 index 00000000000000..3ba63a561bed5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_qqp_w05230505_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_finetuned_qqp_w05230505 BertForSequenceClassification from w05230505 +author: John Snow Labs +name: bert_base_cased_finetuned_qqp_w05230505 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_qqp_w05230505` is a English model originally trained by w05230505. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_qqp_w05230505_en_5.5.0_3.0_1727406510162.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_qqp_w05230505_en_5.5.0_3.0_1727406510162.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_base_cased_finetuned_qqp_w05230505","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetuned_qqp_w05230505", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_qqp_w05230505| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/w05230505/bert-base-cased-finetuned-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_qqp_w05230505_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_qqp_w05230505_pipeline_en.md new file mode 100644 index 00000000000000..bbb4ac1bfd5d27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_finetuned_qqp_w05230505_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_finetuned_qqp_w05230505_pipeline pipeline BertForSequenceClassification from w05230505 +author: John Snow Labs +name: bert_base_cased_finetuned_qqp_w05230505_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_qqp_w05230505_pipeline` is a English model originally trained by w05230505. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_qqp_w05230505_pipeline_en_5.5.0_3.0_1727406531272.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_qqp_w05230505_pipeline_en_5.5.0_3.0_1727406531272.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_finetuned_qqp_w05230505_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_finetuned_qqp_w05230505_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_qqp_w05230505_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/w05230505/bert-base-cased-finetuned-qqp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_ft5_3ep_s42_v2_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_ft5_3ep_s42_v2_en.md new file mode 100644 index 00000000000000..7c0dcb773bebc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_ft5_3ep_s42_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_ft5_3ep_s42_v2 BertForSequenceClassification from AbhishekkV19 +author: John Snow Labs +name: bert_base_cased_ft5_3ep_s42_v2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ft5_3ep_s42_v2` is a English model originally trained by AbhishekkV19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft5_3ep_s42_v2_en_5.5.0_3.0_1727416580228.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft5_3ep_s42_v2_en_5.5.0_3.0_1727416580228.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_base_cased_ft5_3ep_s42_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_ft5_3ep_s42_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_ft5_3ep_s42_v2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/AbhishekkV19/bert-base-cased-ft5-3ep-s42-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline_en.md new file mode 100644 index 00000000000000..a72152f5943800 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline pipeline BertForSequenceClassification from AbhishekkV19 +author: John Snow Labs +name: bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline` is a English model originally trained by AbhishekkV19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline_en_5.5.0_3.0_1727415714451.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline_en_5.5.0_3.0_1727415714451.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_ft5_topless_sent_removed_3ep_s42_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/AbhishekkV19/bert-base-cased-ft5-topless-sent-removed-3ep-s42 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_k4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_k4_pipeline_en.md new file mode 100644 index 00000000000000..10ea574a5a6b98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_k4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_k4_pipeline pipeline BertForSequenceClassification from dtorber +author: John Snow Labs +name: bert_base_cased_k4_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_k4_pipeline` is a English model originally trained by dtorber. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_k4_pipeline_en_5.5.0_3.0_1727412957369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_k4_pipeline_en_5.5.0_3.0_1727412957369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_k4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_k4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_k4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/dtorber/bert-base-cased_K4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaggle_twitter_small_finetuned_clf_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaggle_twitter_small_finetuned_clf_en.md new file mode 100644 index 00000000000000..fa3d0c69c467c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaggle_twitter_small_finetuned_clf_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_kaggle_twitter_small_finetuned_clf BertForSequenceClassification from zloelias +author: John Snow Labs +name: bert_base_cased_kaggle_twitter_small_finetuned_clf +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_kaggle_twitter_small_finetuned_clf` is a English model originally trained by zloelias. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_kaggle_twitter_small_finetuned_clf_en_5.5.0_3.0_1727406681431.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_kaggle_twitter_small_finetuned_clf_en_5.5.0_3.0_1727406681431.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_base_cased_kaggle_twitter_small_finetuned_clf","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_kaggle_twitter_small_finetuned_clf", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_kaggle_twitter_small_finetuned_clf| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|402.9 MB| + +## References + +https://huggingface.co/zloelias/bert-base-cased-kaggle_twitter_small-finetuned-clf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline_en.md new file mode 100644 index 00000000000000..bf34b737e66a43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline pipeline BertForSequenceClassification from zloelias +author: John Snow Labs +name: bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline` is a English model originally trained by zloelias. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline_en_5.5.0_3.0_1727406707099.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline_en_5.5.0_3.0_1727406707099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_kaggle_twitter_small_finetuned_clf_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|402.9 MB| + +## References + +https://huggingface.co/zloelias/bert-base-cased-kaggle_twitter_small-finetuned-clf + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaikouraearthquake_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaikouraearthquake_en.md new file mode 100644 index 00000000000000..1c19392714ba43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaikouraearthquake_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_kaikouraearthquake BertForSequenceClassification from rizvi-rahil786 +author: John Snow Labs +name: bert_base_cased_kaikouraearthquake +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_kaikouraearthquake` is a English model originally trained by rizvi-rahil786. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_kaikouraearthquake_en_5.5.0_3.0_1727418297583.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_kaikouraearthquake_en_5.5.0_3.0_1727418297583.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_base_cased_kaikouraearthquake","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_kaikouraearthquake", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_kaikouraearthquake| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/rizvi-rahil786/bert-base-cased-kaikouraEarthquake \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaikouraearthquake_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaikouraearthquake_pipeline_en.md new file mode 100644 index 00000000000000..221f8a86096fe4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_kaikouraearthquake_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_kaikouraearthquake_pipeline pipeline BertForSequenceClassification from rizvi-rahil786 +author: John Snow Labs +name: bert_base_cased_kaikouraearthquake_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_kaikouraearthquake_pipeline` is a English model originally trained by rizvi-rahil786. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_kaikouraearthquake_pipeline_en_5.5.0_3.0_1727418321221.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_kaikouraearthquake_pipeline_en_5.5.0_3.0_1727418321221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_kaikouraearthquake_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_kaikouraearthquake_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_kaikouraearthquake_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/rizvi-rahil786/bert-base-cased-kaikouraEarthquake + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_mnli_model6_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_mnli_model6_en.md new file mode 100644 index 00000000000000..4f8b989ec8108b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_mnli_model6_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_mnli_model6 BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_mnli_model6 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_model6` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_model6_en_5.5.0_3.0_1727419464796.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_model6_en_5.5.0_3.0_1727419464796.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_base_cased_mnli_model6","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_mnli_model6", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_mnli_model6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-mnli-model6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_mnli_model6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_mnli_model6_pipeline_en.md new file mode 100644 index 00000000000000..15950082e90ac7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_mnli_model6_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_mnli_model6_pipeline pipeline BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_mnli_model6_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_mnli_model6_pipeline` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_model6_pipeline_en_5.5.0_3.0_1727419492904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_model6_pipeline_en_5.5.0_3.0_1727419492904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_mnli_model6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_mnli_model6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_mnli_model6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-mnli-model6 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model1_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model1_en.md new file mode 100644 index 00000000000000..c21ccc408e75de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_snli_model1 BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_snli_model1 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_snli_model1` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model1_en_5.5.0_3.0_1727407074632.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model1_en_5.5.0_3.0_1727407074632.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_base_cased_snli_model1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_snli_model1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_snli_model1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-snli-model1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model2_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model2_en.md new file mode 100644 index 00000000000000..c502390460fc48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_snli_model2 BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_snli_model2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_snli_model2` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model2_en_5.5.0_3.0_1727410424034.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model2_en_5.5.0_3.0_1727410424034.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_base_cased_snli_model2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_snli_model2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_snli_model2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-snli-model2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model2_pipeline_en.md new file mode 100644 index 00000000000000..37f0e4f3def17a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_snli_model2_pipeline pipeline BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_snli_model2_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_snli_model2_pipeline` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model2_pipeline_en_5.5.0_3.0_1727410447180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model2_pipeline_en_5.5.0_3.0_1727410447180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_snli_model2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_snli_model2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_snli_model2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-snli-model2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model3_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model3_en.md new file mode 100644 index 00000000000000..1d8e86aa14bb41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_snli_model3 BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_snli_model3 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_snli_model3` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model3_en_5.5.0_3.0_1727414191727.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model3_en_5.5.0_3.0_1727414191727.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_base_cased_snli_model3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_snli_model3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_snli_model3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-snli-model3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model3_pipeline_en.md new file mode 100644 index 00000000000000..ff8771b7ba8100 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_snli_model3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_snli_model3_pipeline pipeline BertForSequenceClassification from varun-v-rao +author: John Snow Labs +name: bert_base_cased_snli_model3_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_snli_model3_pipeline` is a English model originally trained by varun-v-rao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model3_pipeline_en_5.5.0_3.0_1727414212897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_snli_model3_pipeline_en_5.5.0_3.0_1727414212897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_snli_model3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_snli_model3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_snli_model3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/varun-v-rao/bert-base-cased-snli-model3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_sts_b_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_sts_b_pipeline_en.md new file mode 100644 index 00000000000000..10cc9b55ce1c9f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_cased_sts_b_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_sts_b_pipeline pipeline BertForSequenceClassification from textattack +author: John Snow Labs +name: bert_base_cased_sts_b_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_sts_b_pipeline` is a English model originally trained by textattack. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_sts_b_pipeline_en_5.5.0_3.0_1727412230287.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_sts_b_pipeline_en_5.5.0_3.0_1727412230287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_sts_b_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_sts_b_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_sts_b_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/textattack/bert-base-cased-STS-B + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_3060textsort_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_3060textsort_pipeline_en.md new file mode 100644 index 00000000000000..27663a9e64a076 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_3060textsort_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_3060textsort_pipeline pipeline BertForSequenceClassification from LIJIAQI +author: John Snow Labs +name: bert_base_chinese_3060textsort_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_3060textsort_pipeline` is a English model originally trained by LIJIAQI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_3060textsort_pipeline_en_5.5.0_3.0_1727411614598.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_3060textsort_pipeline_en_5.5.0_3.0_1727411614598.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_3060textsort_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_3060textsort_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_3060textsort_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/LIJIAQI/bert-base-chinese-3060TextSort + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_climate_related_prediction_vv1_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_climate_related_prediction_vv1_en.md new file mode 100644 index 00000000000000..edea16b2b60ebe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_climate_related_prediction_vv1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_climate_related_prediction_vv1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_related_prediction_vv1 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_climate_related_prediction_vv1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_vv1_en_5.5.0_3.0_1727415356669.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_related_prediction_vv1_en_5.5.0_3.0_1727415356669.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_base_chinese_climate_related_prediction_vv1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_climate_related_prediction_vv1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_related_prediction_vv1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-related-prediction-vv1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline_en.md new file mode 100644 index 00000000000000..ede93401181b86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline_en_5.5.0_3.0_1727412805822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline_en_5.5.0_3.0_1727412805822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_climate_risk_opportunity_prediction_v3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-climate-risk-opportunity-prediction-v3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_finetuned_chnsenti_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_finetuned_chnsenti_pipeline_en.md new file mode 100644 index 00000000000000..b0253631616c75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_finetuned_chnsenti_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_chnsenti_pipeline pipeline BertForSequenceClassification from luckydog +author: John Snow Labs +name: bert_base_chinese_finetuned_chnsenti_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_chnsenti_pipeline` is a English model originally trained by luckydog. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_chnsenti_pipeline_en_5.5.0_3.0_1727412036931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_chnsenti_pipeline_en_5.5.0_3.0_1727412036931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_finetuned_chnsenti_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_finetuned_chnsenti_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_chnsenti_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/luckydog/bert-base-chinese-finetuned-ChnSenti + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline_en.md new file mode 100644 index 00000000000000..c3f9ee40ba48f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline pipeline BertForSequenceClassification from r10521708 +author: John Snow Labs +name: bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline` is a English model originally trained by r10521708. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline_en_5.5.0_3.0_1727412465175.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline_en_5.5.0_3.0_1727412465175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_qqp_fhtm_5x_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/r10521708/bert-base-chinese-finetuned-qqp-FHTM-5x + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_emotion_intent_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_emotion_intent_en.md new file mode 100644 index 00000000000000..b6b69086716ad1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_emotion_intent_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_emotion_intent BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_emotion_intent +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_intent` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_emotion_intent_en_5.5.0_3.0_1727407212967.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_emotion_intent_en_5.5.0_3.0_1727407212967.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_base_emotion_intent","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_emotion_intent", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_emotion_intent| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-emotion-intent \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_emotion_intent_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_emotion_intent_pipeline_en.md new file mode 100644 index 00000000000000..78e3b3cabdf4d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_emotion_intent_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_emotion_intent_pipeline pipeline BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_emotion_intent_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_emotion_intent_pipeline` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_emotion_intent_pipeline_en_5.5.0_3.0_1727407237161.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_emotion_intent_pipeline_en_5.5.0_3.0_1727407237161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_emotion_intent_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_emotion_intent_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_emotion_intent_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-emotion-intent + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_enth77_banking_pt2_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_enth77_banking_pt2_en.md new file mode 100644 index 00000000000000..868e27c1c35842 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_enth77_banking_pt2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_enth77_banking_pt2 BertForSequenceClassification from YUCHUL +author: John Snow Labs +name: bert_base_enth77_banking_pt2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_enth77_banking_pt2` is a English model originally trained by YUCHUL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_enth77_banking_pt2_en_5.5.0_3.0_1727405538753.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_enth77_banking_pt2_en_5.5.0_3.0_1727405538753.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_base_enth77_banking_pt2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_enth77_banking_pt2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_enth77_banking_pt2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/YUCHUL/bert-base-enth77-banking-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_finetuned_ynat_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_finetuned_ynat_pipeline_ko.md new file mode 100644 index 00000000000000..4b3fc95dd8062f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_finetuned_ynat_pipeline_ko.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Korean bert_base_finetuned_ynat_pipeline pipeline BertForSequenceClassification from Doowon96 +author: John Snow Labs +name: bert_base_finetuned_ynat_pipeline +date: 2024-09-27 +tags: [ko, open_source, pipeline, onnx] +task: Text Classification +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_ynat_pipeline` is a Korean model originally trained by Doowon96. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_pipeline_ko_5.5.0_3.0_1727418438144.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_pipeline_ko_5.5.0_3.0_1727418438144.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_finetuned_ynat_pipeline", lang = "ko") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_finetuned_ynat_pipeline", lang = "ko") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_ynat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ko| +|Size:|414.7 MB| + +## References + +https://huggingface.co/Doowon96/bert-base-finetuned-ynat + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_galician_cased_finetuned_cola_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_galician_cased_finetuned_cola_pipeline_en.md new file mode 100644 index 00000000000000..6b5e2ac04d4d7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_galician_cased_finetuned_cola_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_galician_cased_finetuned_cola_pipeline pipeline BertForSequenceClassification from gamallo +author: John Snow Labs +name: bert_base_galician_cased_finetuned_cola_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_galician_cased_finetuned_cola_pipeline` is a English model originally trained by gamallo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_galician_cased_finetuned_cola_pipeline_en_5.5.0_3.0_1727403790602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_galician_cased_finetuned_cola_pipeline_en_5.5.0_3.0_1727403790602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_galician_cased_finetuned_cola_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_galician_cased_finetuned_cola_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_galician_cased_finetuned_cola_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|666.7 MB| + +## References + +https://huggingface.co/gamallo/bert-base-gl-cased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_en.md new file mode 100644 index 00000000000000..1d45c7a64d681c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories BertForSequenceClassification from nillo36 +author: John Snow Labs +name: bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_finetuned_tagesschau_subcategories` is a English model originally trained by nillo36. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_en_5.5.0_3.0_1727417608542.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_en_5.5.0_3.0_1727417608542.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_base_german_cased_gnad10_finetuned_tagesschau_subcategories","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.1 MB| + +## References + +https://huggingface.co/nillo36/bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline_en.md new file mode 100644 index 00000000000000..0830190a458337 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline pipeline BertForSequenceClassification from nillo36 +author: John Snow Labs +name: bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline` is a English model originally trained by nillo36. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline_en_5.5.0_3.0_1727417629419.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline_en_5.5.0_3.0_1727417629419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_german_cased_gnad10_finetuned_tagesschau_subcategories_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.1 MB| + +## References + +https://huggingface.co/nillo36/bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_klue_ynat_finetuned_jihoonkimharu_ko.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_klue_ynat_finetuned_jihoonkimharu_ko.md new file mode 100644 index 00000000000000..364449f400a726 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_klue_ynat_finetuned_jihoonkimharu_ko.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Korean bert_base_klue_ynat_finetuned_jihoonkimharu BertForSequenceClassification from jihoonkimharu +author: John Snow Labs +name: bert_base_klue_ynat_finetuned_jihoonkimharu +date: 2024-09-27 +tags: [ko, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_klue_ynat_finetuned_jihoonkimharu` is a Korean model originally trained by jihoonkimharu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_klue_ynat_finetuned_jihoonkimharu_ko_5.5.0_3.0_1727408196313.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_klue_ynat_finetuned_jihoonkimharu_ko_5.5.0_3.0_1727408196313.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_base_klue_ynat_finetuned_jihoonkimharu","ko") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_klue_ynat_finetuned_jihoonkimharu", "ko") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_klue_ynat_finetuned_jihoonkimharu| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ko| +|Size:|414.7 MB| + +## References + +https://huggingface.co/jihoonkimharu/bert-base-klue-ynat-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline_ko.md new file mode 100644 index 00000000000000..4f24f701222049 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline_ko.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Korean bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline pipeline BertForSequenceClassification from jihoonkimharu +author: John Snow Labs +name: bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline +date: 2024-09-27 +tags: [ko, open_source, pipeline, onnx] +task: Text Classification +language: ko +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline` is a Korean model originally trained by jihoonkimharu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline_ko_5.5.0_3.0_1727408223051.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline_ko_5.5.0_3.0_1727408223051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline", lang = "ko") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline", lang = "ko") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_klue_ynat_finetuned_jihoonkimharu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ko| +|Size:|414.7 MB| + +## References + +https://huggingface.co/jihoonkimharu/bert-base-klue-ynat-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_msmarco_fiqa_transfer_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_msmarco_fiqa_transfer_pipeline_en.md new file mode 100644 index 00000000000000..039c338bddd930 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_msmarco_fiqa_transfer_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_msmarco_fiqa_transfer_pipeline pipeline BertForSequenceClassification from vittoriomaggio +author: John Snow Labs +name: bert_base_msmarco_fiqa_transfer_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_msmarco_fiqa_transfer_pipeline` is a English model originally trained by vittoriomaggio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_msmarco_fiqa_transfer_pipeline_en_5.5.0_3.0_1727411075227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_msmarco_fiqa_transfer_pipeline_en_5.5.0_3.0_1727411075227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_msmarco_fiqa_transfer_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_msmarco_fiqa_transfer_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_msmarco_fiqa_transfer_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/vittoriomaggio/bert-base-msmarco-fiqa-transfer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_7xan7der7_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_7xan7der7_pipeline_xx.md new file mode 100644 index 00000000000000..7b38bc40d0cf4a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_7xan7der7_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_7xan7der7_pipeline pipeline BertForSequenceClassification from 7Xan7der7 +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_7xan7der7_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_7xan7der7_pipeline` is a Multilingual model originally trained by 7Xan7der7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_7xan7der7_pipeline_xx_5.5.0_3.0_1727405736960.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_7xan7der7_pipeline_xx_5.5.0_3.0_1727405736960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_7xan7der7_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_7xan7der7_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_7xan7der7_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/7Xan7der7/bert-base-multilingual-cased-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline_xx.md new file mode 100644 index 00000000000000..1a8cdbc2e030c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline pipeline BertForSequenceClassification from Poulami +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline` is a Multilingual model originally trained by Poulami. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline_xx_5.5.0_3.0_1727402001461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline_xx_5.5.0_3.0_1727402001461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_paraphrase_pawsx_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Poulami/bert-base-multilingual-cased-finetuned-paraphrase-PAWSX-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline_xx.md new file mode 100644 index 00000000000000..b88fe0d53f5346 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline pipeline BertForSequenceClassification from DiederikMartens +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline` is a Multilingual model originally trained by DiederikMartens. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline_xx_5.5.0_3.0_1727413931080.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline_xx_5.5.0_3.0_1727413931080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_sa5_model_output_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/DiederikMartens/bert-base-multilingual-cased-finetuned-sa5-model_output + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline_xx.md new file mode 100644 index 00000000000000..3934a3283e107e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline pipeline BertForSequenceClassification from w11wo +author: John Snow Labs +name: bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline` is a Multilingual model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline_xx_5.5.0_3.0_1727417827404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline_xx_5.5.0_3.0_1727417827404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_twitter_indonesia_sarcastic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/w11wo/bert-base-multilingual-cased-twitter-indonesia-sarcastic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_twitter_indonesia_sarcastic_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_twitter_indonesia_sarcastic_xx.md new file mode 100644 index 00000000000000..22eab8010d8306 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_twitter_indonesia_sarcastic_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_twitter_indonesia_sarcastic BertForSequenceClassification from w11wo +author: John Snow Labs +name: bert_base_multilingual_cased_twitter_indonesia_sarcastic +date: 2024-09-27 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_twitter_indonesia_sarcastic` is a Multilingual model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_twitter_indonesia_sarcastic_xx_5.5.0_3.0_1727417788979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_twitter_indonesia_sarcastic_xx_5.5.0_3.0_1727417788979.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_base_multilingual_cased_twitter_indonesia_sarcastic","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_twitter_indonesia_sarcastic", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_twitter_indonesia_sarcastic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/w11wo/bert-base-multilingual-cased-twitter-indonesia-sarcastic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_vsmec_100_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_vsmec_100_pipeline_xx.md new file mode 100644 index 00000000000000..f1a8ceec9f4490 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_cased_vsmec_100_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_vsmec_100_pipeline pipeline BertForSequenceClassification from tmnam20 +author: John Snow Labs +name: bert_base_multilingual_cased_vsmec_100_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_vsmec_100_pipeline` is a Multilingual model originally trained by tmnam20. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_vsmec_100_pipeline_xx_5.5.0_3.0_1727408263188.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_vsmec_100_pipeline_xx_5.5.0_3.0_1727408263188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_cased_vsmec_100_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_cased_vsmec_100_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_vsmec_100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/tmnam20/bert-base-multilingual-cased-vsmec-100 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_dhpitt_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_dhpitt_pipeline_xx.md new file mode 100644 index 00000000000000..144fa296d0adb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_dhpitt_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_dhpitt_pipeline pipeline BertForSequenceClassification from dhpitt +author: John Snow Labs +name: bert_base_multilingual_uncased_dhpitt_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_dhpitt_pipeline` is a Multilingual model originally trained by dhpitt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_dhpitt_pipeline_xx_5.5.0_3.0_1727418608689.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_dhpitt_pipeline_xx_5.5.0_3.0_1727418608689.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_uncased_dhpitt_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_uncased_dhpitt_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_dhpitt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/dhpitt/bert-base-multilingual-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_dhpitt_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_dhpitt_xx.md new file mode 100644 index 00000000000000..463f6f888fd4b9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_dhpitt_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_dhpitt BertForSequenceClassification from dhpitt +author: John Snow Labs +name: bert_base_multilingual_uncased_dhpitt +date: 2024-09-27 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_dhpitt` is a Multilingual model originally trained by dhpitt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_dhpitt_xx_5.5.0_3.0_1727418576479.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_dhpitt_xx_5.5.0_3.0_1727418576479.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_base_multilingual_uncased_dhpitt","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_dhpitt", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_dhpitt| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/dhpitt/bert-base-multilingual-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline_xx.md new file mode 100644 index 00000000000000..430ee4335275e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline pipeline BertForSequenceClassification from abirmondalind +author: John Snow Labs +name: bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline` is a Multilingual model originally trained by abirmondalind. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline_xx_5.5.0_3.0_1727413956163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline_xx_5.5.0_3.0_1727413956163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_hate_speech_ben_hin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/abirmondalind/bert-base-multilingual-uncased-hate-speech-ben-hin + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_hate_speech_ben_hin_xx.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_hate_speech_ben_hin_xx.md new file mode 100644 index 00000000000000..2d0465b94e5b8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_multilingual_uncased_hate_speech_ben_hin_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_hate_speech_ben_hin BertForSequenceClassification from abirmondalind +author: John Snow Labs +name: bert_base_multilingual_uncased_hate_speech_ben_hin +date: 2024-09-27 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_hate_speech_ben_hin` is a Multilingual model originally trained by abirmondalind. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_hate_speech_ben_hin_xx_5.5.0_3.0_1727413923701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_hate_speech_ben_hin_xx_5.5.0_3.0_1727413923701.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_base_multilingual_uncased_hate_speech_ben_hin","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_hate_speech_ben_hin", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_hate_speech_ben_hin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/abirmondalind/bert-base-multilingual-uncased-hate-speech-ben-hin \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_nli_theseus_bulgarian_pipeline_bg.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_nli_theseus_bulgarian_pipeline_bg.md new file mode 100644 index 00000000000000..51e64f7131b04a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_nli_theseus_bulgarian_pipeline_bg.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Bulgarian bert_base_nli_theseus_bulgarian_pipeline pipeline BertForSequenceClassification from rmihaylov +author: John Snow Labs +name: bert_base_nli_theseus_bulgarian_pipeline +date: 2024-09-27 +tags: [bg, open_source, pipeline, onnx] +task: Text Classification +language: bg +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_nli_theseus_bulgarian_pipeline` is a Bulgarian model originally trained by rmihaylov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_nli_theseus_bulgarian_pipeline_bg_5.5.0_3.0_1727399023527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_nli_theseus_bulgarian_pipeline_bg_5.5.0_3.0_1727399023527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_nli_theseus_bulgarian_pipeline", lang = "bg") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_nli_theseus_bulgarian_pipeline", lang = "bg") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_nli_theseus_bulgarian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|bg| +|Size:|507.9 MB| + +## References + +https://huggingface.co/rmihaylov/bert-base-nli-theseus-bg + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_phia_test_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_phia_test_en.md new file mode 100644 index 00000000000000..f487b3aa998989 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_phia_test_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_phia_test BertForSequenceClassification from reiffd +author: John Snow Labs +name: bert_base_phia_test +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_phia_test` is a English model originally trained by reiffd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_phia_test_en_5.5.0_3.0_1727405021846.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_phia_test_en_5.5.0_3.0_1727405021846.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_base_phia_test","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_phia_test", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_phia_test| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/reiffd/bert-base-phia-test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_phia_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_phia_test_pipeline_en.md new file mode 100644 index 00000000000000..2638492afc41e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_phia_test_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_phia_test_pipeline pipeline BertForSequenceClassification from reiffd +author: John Snow Labs +name: bert_base_phia_test_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_phia_test_pipeline` is a English model originally trained by reiffd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_phia_test_pipeline_en_5.5.0_3.0_1727405043553.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_phia_test_pipeline_en_5.5.0_3.0_1727405043553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_phia_test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_phia_test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_phia_test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/reiffd/bert-base-phia-test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_qqp_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_qqp_en.md new file mode 100644 index 00000000000000..dec3fb5f94fc59 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_qqp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_qqp BertForSequenceClassification from Cheng98 +author: John Snow Labs +name: bert_base_qqp +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_qqp` is a English model originally trained by Cheng98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_qqp_en_5.5.0_3.0_1727417674231.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_qqp_en_5.5.0_3.0_1727417674231.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_base_qqp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_qqp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_qqp| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Cheng98/bert-base-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_qqp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_qqp_pipeline_en.md new file mode 100644 index 00000000000000..5f89fbc2f41b91 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_qqp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_qqp_pipeline pipeline BertForSequenceClassification from Cheng98 +author: John Snow Labs +name: bert_base_qqp_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_qqp_pipeline` is a English model originally trained by Cheng98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_qqp_pipeline_en_5.5.0_3.0_1727417694987.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_qqp_pipeline_en_5.5.0_3.0_1727417694987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_qqp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_qqp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_qqp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Cheng98/bert-base-qqp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_trec_question_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_trec_question_classification_en.md new file mode 100644 index 00000000000000..b92fddfcab001c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_trec_question_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_trec_question_classification BertForSequenceClassification from carrassi-ni +author: John Snow Labs +name: bert_base_trec_question_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_trec_question_classification` is a English model originally trained by carrassi-ni. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_trec_question_classification_en_5.5.0_3.0_1727406419269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_trec_question_classification_en_5.5.0_3.0_1727406419269.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_base_trec_question_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_trec_question_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_trec_question_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/carrassi-ni/bert-base-trec-question-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_trec_question_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_trec_question_classification_pipeline_en.md new file mode 100644 index 00000000000000..52b3629f4bf56a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_trec_question_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_trec_question_classification_pipeline pipeline BertForSequenceClassification from carrassi-ni +author: John Snow Labs +name: bert_base_trec_question_classification_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_trec_question_classification_pipeline` is a English model originally trained by carrassi-ni. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_trec_question_classification_pipeline_en_5.5.0_3.0_1727406443471.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_trec_question_classification_pipeline_en_5.5.0_3.0_1727406443471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_trec_question_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_trec_question_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_trec_question_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/carrassi-ni/bert-base-trec-question-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_turkish_128k_uncased_offensive_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_turkish_128k_uncased_offensive_pipeline_tr.md new file mode 100644 index 00000000000000..a3a1f48eab05ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_turkish_128k_uncased_offensive_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish bert_base_turkish_128k_uncased_offensive_pipeline pipeline BertForSequenceClassification from Overfit-GM +author: John Snow Labs +name: bert_base_turkish_128k_uncased_offensive_pipeline +date: 2024-09-27 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_turkish_128k_uncased_offensive_pipeline` is a Turkish model originally trained by Overfit-GM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_128k_uncased_offensive_pipeline_tr_5.5.0_3.0_1727409450409.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_128k_uncased_offensive_pipeline_tr_5.5.0_3.0_1727409450409.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_turkish_128k_uncased_offensive_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_turkish_128k_uncased_offensive_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_128k_uncased_offensive_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|691.6 MB| + +## References + +https://huggingface.co/Overfit-GM/bert-base-turkish-128k-uncased-offensive + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_turkish_uncased_offensive_tr.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_turkish_uncased_offensive_tr.md new file mode 100644 index 00000000000000..b31319936ee441 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_turkish_uncased_offensive_tr.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Turkish bert_base_turkish_uncased_offensive BertForSequenceClassification from Overfit-GM +author: John Snow Labs +name: bert_base_turkish_uncased_offensive +date: 2024-09-27 +tags: [tr, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_turkish_uncased_offensive` is a Turkish model originally trained by Overfit-GM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_turkish_uncased_offensive_tr_5.5.0_3.0_1727401415011.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_turkish_uncased_offensive_tr_5.5.0_3.0_1727401415011.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_base_turkish_uncased_offensive","tr") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_turkish_uncased_offensive", "tr") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_turkish_uncased_offensive| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|414.7 MB| + +## References + +https://huggingface.co/Overfit-GM/bert-base-turkish-uncased-offensive \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_2_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_2_en.md new file mode 100644 index 00000000000000..cbdb2b09a05f8f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_2 BertForSequenceClassification from UchihaMadara +author: John Snow Labs +name: bert_base_uncased_2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_2` is a English model originally trained by UchihaMadara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_2_en_5.5.0_3.0_1727418765159.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_2_en_5.5.0_3.0_1727418765159.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_base_uncased_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/UchihaMadara/bert-base-uncased-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_2_pipeline_en.md new file mode 100644 index 00000000000000..d5d7932eb3c8c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_2_pipeline pipeline BertForSequenceClassification from UchihaMadara +author: John Snow Labs +name: bert_base_uncased_2_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_2_pipeline` is a English model originally trained by UchihaMadara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_2_pipeline_en_5.5.0_3.0_1727418789260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_2_pipeline_en_5.5.0_3.0_1727418789260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/UchihaMadara/bert-base-uncased-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_amazon_reviews_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_amazon_reviews_sentiment_analysis_en.md new file mode 100644 index 00000000000000..3b1c567d1f5550 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_amazon_reviews_sentiment_analysis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_amazon_reviews_sentiment_analysis BertForSequenceClassification from ckandemir +author: John Snow Labs +name: bert_base_uncased_amazon_reviews_sentiment_analysis +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_amazon_reviews_sentiment_analysis` is a English model originally trained by ckandemir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_amazon_reviews_sentiment_analysis_en_5.5.0_3.0_1727413426391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_amazon_reviews_sentiment_analysis_en_5.5.0_3.0_1727413426391.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_base_uncased_amazon_reviews_sentiment_analysis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_amazon_reviews_sentiment_analysis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_amazon_reviews_sentiment_analysis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ckandemir/bert-base-uncased-amazon-reviews-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_apple_iphone_northern_sami_reviews_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_apple_iphone_northern_sami_reviews_en.md new file mode 100644 index 00000000000000..90d5cf342b1d80 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_apple_iphone_northern_sami_reviews_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_apple_iphone_northern_sami_reviews BertForSequenceClassification from DunnBC22 +author: John Snow Labs +name: bert_base_uncased_apple_iphone_northern_sami_reviews +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_apple_iphone_northern_sami_reviews` is a English model originally trained by DunnBC22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_apple_iphone_northern_sami_reviews_en_5.5.0_3.0_1727408643190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_apple_iphone_northern_sami_reviews_en_5.5.0_3.0_1727408643190.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_base_uncased_apple_iphone_northern_sami_reviews","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_apple_iphone_northern_sami_reviews", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_apple_iphone_northern_sami_reviews| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DunnBC22/bert-base-uncased-apple_iphone_se_reviews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline_en.md new file mode 100644 index 00000000000000..70cce47a6813bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline pipeline BertForSequenceClassification from DunnBC22 +author: John Snow Labs +name: bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline` is a English model originally trained by DunnBC22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline_en_5.5.0_3.0_1727408668923.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline_en_5.5.0_3.0_1727408668923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_apple_iphone_northern_sami_reviews_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DunnBC22/bert-base-uncased-apple_iphone_se_reviews + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_brenomatos_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_brenomatos_pipeline_en.md new file mode 100644 index 00000000000000..2a912461069c69 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_brenomatos_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_brenomatos_pipeline pipeline BertForSequenceClassification from brenomatos +author: John Snow Labs +name: bert_base_uncased_brenomatos_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_brenomatos_pipeline` is a English model originally trained by brenomatos. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_brenomatos_pipeline_en_5.5.0_3.0_1727404882955.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_brenomatos_pipeline_en_5.5.0_3.0_1727404882955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_brenomatos_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_brenomatos_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_brenomatos_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/brenomatos/bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_clickbait_keywords_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_clickbait_keywords_en.md new file mode 100644 index 00000000000000..95ad4e2773e2cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_clickbait_keywords_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_clickbait_keywords BertForSequenceClassification from Stremie +author: John Snow Labs +name: bert_base_uncased_clickbait_keywords +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_clickbait_keywords` is a English model originally trained by Stremie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_clickbait_keywords_en_5.5.0_3.0_1727407401415.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_clickbait_keywords_en_5.5.0_3.0_1727407401415.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_base_uncased_clickbait_keywords","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_clickbait_keywords", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_clickbait_keywords| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Stremie/bert-base-uncased-clickbait-keywords \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_clickbait_keywords_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_clickbait_keywords_pipeline_en.md new file mode 100644 index 00000000000000..b2b81c762438c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_clickbait_keywords_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_clickbait_keywords_pipeline pipeline BertForSequenceClassification from Stremie +author: John Snow Labs +name: bert_base_uncased_clickbait_keywords_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_clickbait_keywords_pipeline` is a English model originally trained by Stremie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_clickbait_keywords_pipeline_en_5.5.0_3.0_1727407422367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_clickbait_keywords_pipeline_en_5.5.0_3.0_1727407422367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_clickbait_keywords_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_clickbait_keywords_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_clickbait_keywords_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Stremie/bert-base-uncased-clickbait-keywords + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_cloth_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_cloth_pipeline_en.md new file mode 100644 index 00000000000000..455f18a52d5d51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_cloth_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_cloth_pipeline pipeline BertForSequenceClassification from howey +author: John Snow Labs +name: bert_base_uncased_cloth_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_cloth_pipeline` is a English model originally trained by howey. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cloth_pipeline_en_5.5.0_3.0_1727401440248.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cloth_pipeline_en_5.5.0_3.0_1727401440248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_cloth_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_cloth_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cloth_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/howey/bert-base-uncased-cloth + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_batchsize_cola_16_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_batchsize_cola_16_en.md new file mode 100644 index 00000000000000..bd34d773e422fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_batchsize_cola_16_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_batchsize_cola_16 BertForSequenceClassification from yagmurery +author: John Snow Labs +name: bert_base_uncased_finetuned_batchsize_cola_16 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_batchsize_cola_16` is a English model originally trained by yagmurery. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_batchsize_cola_16_en_5.5.0_3.0_1727417193603.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_batchsize_cola_16_en_5.5.0_3.0_1727417193603.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_base_uncased_finetuned_batchsize_cola_16","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_batchsize_cola_16", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_batchsize_cola_16| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yagmurery/bert-base-uncased-finetuned-batchSize-cola-16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_batchsize_cola_16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_batchsize_cola_16_pipeline_en.md new file mode 100644 index 00000000000000..e1de40037a870e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_batchsize_cola_16_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_batchsize_cola_16_pipeline pipeline BertForSequenceClassification from yagmurery +author: John Snow Labs +name: bert_base_uncased_finetuned_batchsize_cola_16_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_batchsize_cola_16_pipeline` is a English model originally trained by yagmurery. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_batchsize_cola_16_pipeline_en_5.5.0_3.0_1727417216712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_batchsize_cola_16_pipeline_en_5.5.0_3.0_1727417216712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_batchsize_cola_16_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_batchsize_cola_16_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_batchsize_cola_16_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yagmurery/bert-base-uncased-finetuned-batchSize-cola-16 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_4bd4774h_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_4bd4774h_pipeline_en.md new file mode 100644 index 00000000000000..5feb7e4efc89d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_4bd4774h_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_4bd4774h_pipeline pipeline BertForSequenceClassification from 4bd4774h +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_4bd4774h_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_4bd4774h_pipeline` is a English model originally trained by 4bd4774h. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_4bd4774h_pipeline_en_5.5.0_3.0_1727415298827.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_4bd4774h_pipeline_en_5.5.0_3.0_1727415298827.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_4bd4774h_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_4bd4774h_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_4bd4774h_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/4bd4774h/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_bilginn_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_bilginn_en.md new file mode 100644 index 00000000000000..3af2c08ecbf46d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_bilginn_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_bilginn BertForSequenceClassification from bilginn +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_bilginn +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_bilginn` is a English model originally trained by bilginn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_bilginn_en_5.5.0_3.0_1727414175030.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_bilginn_en_5.5.0_3.0_1727414175030.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_base_uncased_finetuned_cola_bilginn","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_bilginn", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_bilginn| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/bilginn/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_cekole_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_cekole_pipeline_en.md new file mode 100644 index 00000000000000..13e86fb83335d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_cekole_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_cekole_pipeline pipeline BertForSequenceClassification from cekole +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_cekole_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_cekole_pipeline` is a English model originally trained by cekole. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_cekole_pipeline_en_5.5.0_3.0_1727405247866.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_cekole_pipeline_en_5.5.0_3.0_1727405247866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_cekole_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_cekole_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_cekole_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cekole/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_1_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_1_en.md new file mode 100644 index 00000000000000..7e7c95687b4866 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_dropout_0_1 BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_dropout_0_1 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_dropout_0_1` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_1_en_5.5.0_3.0_1727411558576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_1_en_5.5.0_3.0_1727411558576.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_base_uncased_finetuned_cola_dropout_0_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_dropout_0_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_dropout_0_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-dropout-0.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_2_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_2_en.md new file mode 100644 index 00000000000000..7f09a346ebd95f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_dropout_0_2 BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_dropout_0_2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_dropout_0_2` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_2_en_5.5.0_3.0_1727411358753.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_2_en_5.5.0_3.0_1727411358753.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_base_uncased_finetuned_cola_dropout_0_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_dropout_0_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_dropout_0_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-dropout-0.2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_2_pipeline_en.md new file mode 100644 index 00000000000000..e1ca038cf0ffaf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_dropout_0_2_pipeline pipeline BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_dropout_0_2_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_dropout_0_2_pipeline` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_2_pipeline_en_5.5.0_3.0_1727411390434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_2_pipeline_en_5.5.0_3.0_1727411390434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_dropout_0_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_dropout_0_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_dropout_0_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-dropout-0.2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_5_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_5_en.md new file mode 100644 index 00000000000000..fc382ccf684ab6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_dropout_0_5 BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_dropout_0_5 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_dropout_0_5` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_5_en_5.5.0_3.0_1727418295966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_5_en_5.5.0_3.0_1727418295966.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_base_uncased_finetuned_cola_dropout_0_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_dropout_0_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_dropout_0_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-dropout-0.5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_5_pipeline_en.md new file mode 100644 index 00000000000000..f2b6bdc55cabce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_dropout_0_5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_dropout_0_5_pipeline pipeline BertForSequenceClassification from cansurav +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_dropout_0_5_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_dropout_0_5_pipeline` is a English model originally trained by cansurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_5_pipeline_en_5.5.0_3.0_1727418320046.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_dropout_0_5_pipeline_en_5.5.0_3.0_1727418320046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_dropout_0_5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_dropout_0_5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_dropout_0_5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/cansurav/bert-base-uncased-finetuned-cola-dropout-0.5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_eceersoyy_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_eceersoyy_en.md new file mode 100644 index 00000000000000..5f21c2cb968607 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_eceersoyy_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_eceersoyy BertForSequenceClassification from eceersoyy +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_eceersoyy +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_eceersoyy` is a English model originally trained by eceersoyy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_eceersoyy_en_5.5.0_3.0_1727417934975.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_eceersoyy_en_5.5.0_3.0_1727417934975.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_base_uncased_finetuned_cola_eceersoyy","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_eceersoyy", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_eceersoyy| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/eceersoyy/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_eceersoyy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_eceersoyy_pipeline_en.md new file mode 100644 index 00000000000000..b6a94a43651dcd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_eceersoyy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_eceersoyy_pipeline pipeline BertForSequenceClassification from eceersoyy +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_eceersoyy_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_eceersoyy_pipeline` is a English model originally trained by eceersoyy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_eceersoyy_pipeline_en_5.5.0_3.0_1727417956275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_eceersoyy_pipeline_en_5.5.0_3.0_1727417956275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_eceersoyy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_eceersoyy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_eceersoyy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/eceersoyy/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline_en.md new file mode 100644 index 00000000000000..03c8620eabc403 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline pipeline BertForSequenceClassification from ertugrulcoban +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline` is a English model originally trained by ertugrulcoban. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline_en_5.5.0_3.0_1727417353555.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline_en_5.5.0_3.0_1727417353555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_ertugrulcoban_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ertugrulcoban/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_farawayxxx_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_farawayxxx_en.md new file mode 100644 index 00000000000000..c1dd1f86e54c0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_farawayxxx_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_farawayxxx BertForSequenceClassification from farawayxxx +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_farawayxxx +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_farawayxxx` is a English model originally trained by farawayxxx. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_farawayxxx_en_5.5.0_3.0_1727416459995.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_farawayxxx_en_5.5.0_3.0_1727416459995.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_base_uncased_finetuned_cola_farawayxxx","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_farawayxxx", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_farawayxxx| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/farawayxxx/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_gursoyy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_gursoyy_pipeline_en.md new file mode 100644 index 00000000000000..12ae5ab7ac315d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_gursoyy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_gursoyy_pipeline pipeline BertForSequenceClassification from Gursoyy +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_gursoyy_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_gursoyy_pipeline` is a English model originally trained by Gursoyy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_gursoyy_pipeline_en_5.5.0_3.0_1727416684673.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_gursoyy_pipeline_en_5.5.0_3.0_1727416684673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_gursoyy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_gursoyy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_gursoyy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Gursoyy/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_ovgumsezen_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_ovgumsezen_en.md new file mode 100644 index 00000000000000..ae5a7546955f79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_ovgumsezen_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_ovgumsezen BertForSequenceClassification from OvgumSezen +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_ovgumsezen +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ovgumsezen` is a English model originally trained by OvgumSezen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ovgumsezen_en_5.5.0_3.0_1727415958375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ovgumsezen_en_5.5.0_3.0_1727415958375.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_base_uncased_finetuned_cola_ovgumsezen","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_ovgumsezen", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_ovgumsezen| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/OvgumSezen/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_rifatozkurt_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_rifatozkurt_en.md new file mode 100644 index 00000000000000..9c731b19113d89 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_rifatozkurt_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_rifatozkurt BertForSequenceClassification from rifatozkurt +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_rifatozkurt +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_rifatozkurt` is a English model originally trained by rifatozkurt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_rifatozkurt_en_5.5.0_3.0_1727400982311.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_rifatozkurt_en_5.5.0_3.0_1727400982311.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_base_uncased_finetuned_cola_rifatozkurt","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_rifatozkurt", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_rifatozkurt| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rifatozkurt/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_rifatozkurt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_rifatozkurt_pipeline_en.md new file mode 100644 index 00000000000000..a0d757d22de59a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_rifatozkurt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_rifatozkurt_pipeline pipeline BertForSequenceClassification from rifatozkurt +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_rifatozkurt_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_rifatozkurt_pipeline` is a English model originally trained by rifatozkurt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_rifatozkurt_pipeline_en_5.5.0_3.0_1727401003147.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_rifatozkurt_pipeline_en_5.5.0_3.0_1727401003147.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_rifatozkurt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_rifatozkurt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_rifatozkurt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rifatozkurt/bert-base-uncased-finetuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_en.md new file mode 100644 index 00000000000000..c1322f59841346 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server BertForSequenceClassification from sepehrbakhshi +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sepehr_sepehr_sepehr_saturday_from_server` is a English model originally trained by sepehrbakhshi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_en_5.5.0_3.0_1727415329827.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_en_5.5.0_3.0_1727415329827.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_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sepehrbakhshi/bert-base-uncased-finetuned-cola_sepehr_sepehr_sepehr_saturday_from_server \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline_en.md new file mode 100644 index 00000000000000..fed5a33f5f4d51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline pipeline BertForSequenceClassification from sepehrbakhshi +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline` is a English model originally trained by sepehrbakhshi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline_en_5.5.0_3.0_1727415351502.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline_en_5.5.0_3.0_1727415351502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_sepehr_sepehr_sepehr_saturday_from_server_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sepehrbakhshi/bert-base-uncased-finetuned-cola_sepehr_sepehr_sepehr_saturday_from_server + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_trying_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_trying_en.md new file mode 100644 index 00000000000000..e3763f5c98c35a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_cola_trying_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_trying BertForSequenceClassification from meltemtatli +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_trying +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_trying` is a English model originally trained by meltemtatli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_trying_en_5.5.0_3.0_1727416339017.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_trying_en_5.5.0_3.0_1727416339017.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_base_uncased_finetuned_cola_trying","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_trying", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_trying| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/meltemtatli/bert-base-uncased-finetuned-cola-trying \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_emotion_jaywang7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_emotion_jaywang7_pipeline_en.md new file mode 100644 index 00000000000000..5e7b5d2e433d1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_emotion_jaywang7_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_emotion_jaywang7_pipeline pipeline BertForSequenceClassification from JayWang7 +author: John Snow Labs +name: bert_base_uncased_finetuned_emotion_jaywang7_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_emotion_jaywang7_pipeline` is a English model originally trained by JayWang7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_emotion_jaywang7_pipeline_en_5.5.0_3.0_1727415179541.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_emotion_jaywang7_pipeline_en_5.5.0_3.0_1727415179541.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_emotion_jaywang7_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_emotion_jaywang7_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_emotion_jaywang7_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JayWang7/bert-base-uncased-finetuned-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_env_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_env_en.md new file mode 100644 index 00000000000000..377735753cf174 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_env_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_env BertForSequenceClassification from lmajer +author: John Snow Labs +name: bert_base_uncased_finetuned_env +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_env` is a English model originally trained by lmajer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_env_en_5.5.0_3.0_1727417300950.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_env_en_5.5.0_3.0_1727417300950.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_base_uncased_finetuned_env","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_env", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_env| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/lmajer/bert-base-uncased-finetuned-ENV \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_env_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_env_pipeline_en.md new file mode 100644 index 00000000000000..71c904e768d8c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_env_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_env_pipeline pipeline BertForSequenceClassification from lmajer +author: John Snow Labs +name: bert_base_uncased_finetuned_env_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_env_pipeline` is a English model originally trained by lmajer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_env_pipeline_en_5.5.0_3.0_1727417322428.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_env_pipeline_en_5.5.0_3.0_1727417322428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_env_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_env_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_env_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/lmajer/bert-base-uncased-finetuned-ENV + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_fin_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_fin_en.md new file mode 100644 index 00000000000000..529353c2693abe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_fin_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_fin BertForSequenceClassification from Venkatesh4342 +author: John Snow Labs +name: bert_base_uncased_finetuned_fin +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_fin` is a English model originally trained by Venkatesh4342. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_fin_en_5.5.0_3.0_1727412866644.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_fin_en_5.5.0_3.0_1727412866644.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_base_uncased_finetuned_fin","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_fin", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_fin| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Venkatesh4342/bert-base-uncased-finetuned-fin \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_imdb_jimmie_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_imdb_jimmie_en.md new file mode 100644 index 00000000000000..43b4bf9bcb650e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_imdb_jimmie_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_imdb_jimmie BertForSequenceClassification from Jimmie +author: John Snow Labs +name: bert_base_uncased_finetuned_imdb_jimmie +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_imdb_jimmie` is a English model originally trained by Jimmie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_imdb_jimmie_en_5.5.0_3.0_1727401554055.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_imdb_jimmie_en_5.5.0_3.0_1727401554055.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_base_uncased_finetuned_imdb_jimmie","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_imdb_jimmie", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_imdb_jimmie| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jimmie/bert-base-uncased-finetuned-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_m_reach_seller_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_m_reach_seller_en.md new file mode 100644 index 00000000000000..6b80ab800649c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_m_reach_seller_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_m_reach_seller BertForSequenceClassification from Gregorig +author: John Snow Labs +name: bert_base_uncased_finetuned_m_reach_seller +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_m_reach_seller` is a English model originally trained by Gregorig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_m_reach_seller_en_5.5.0_3.0_1727406523279.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_m_reach_seller_en_5.5.0_3.0_1727406523279.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_base_uncased_finetuned_m_reach_seller","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_m_reach_seller", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_m_reach_seller| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Gregorig/bert-base-uncased-finetuned-m_reach_seller \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_m_reach_seller_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_m_reach_seller_pipeline_en.md new file mode 100644 index 00000000000000..2211a8a23d7763 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_m_reach_seller_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_m_reach_seller_pipeline pipeline BertForSequenceClassification from Gregorig +author: John Snow Labs +name: bert_base_uncased_finetuned_m_reach_seller_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_m_reach_seller_pipeline` is a English model originally trained by Gregorig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_m_reach_seller_pipeline_en_5.5.0_3.0_1727406544255.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_m_reach_seller_pipeline_en_5.5.0_3.0_1727406544255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_m_reach_seller_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_m_reach_seller_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_m_reach_seller_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Gregorig/bert-base-uncased-finetuned-m_reach_seller + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline_en.md new file mode 100644 index 00000000000000..cb02805a6afa35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline pipeline BertForSequenceClassification from allman +author: John Snow Labs +name: bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline` is a English model originally trained by allman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline_en_5.5.0_3.0_1727417655357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline_en_5.5.0_3.0_1727417655357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_meia_analisisdesentimientos_allman_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/allman/bert-base-uncased-finetuned-MeIA-AnalisisDeSentimientos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_en.md new file mode 100644 index 00000000000000..3b70312cadb2e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_max_length_32_epoch_1 BertForSequenceClassification from yy642 +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_max_length_32_epoch_1 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mnli_max_length_32_epoch_1` is a English model originally trained by yy642. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_en_5.5.0_3.0_1727411027481.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_en_5.5.0_3.0_1727411027481.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_base_uncased_finetuned_mnli_max_length_32_epoch_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mnli_max_length_32_epoch_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_max_length_32_epoch_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-max-length-32-epoch-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline_en.md new file mode 100644 index 00000000000000..a434f6584be2ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline pipeline BertForSequenceClassification from yy642 +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline` is a English model originally trained by yy642. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline_en_5.5.0_3.0_1727411048304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline_en_5.5.0_3.0_1727411048304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_max_length_32_epoch_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-max-length-32-epoch-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_rte_wnli_10_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_rte_wnli_10_en.md new file mode 100644 index 00000000000000..db07c61f0321e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_rte_wnli_10_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_rte_wnli_10 BertForSequenceClassification from yy642 +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_rte_wnli_10 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mnli_rte_wnli_10` is a English model originally trained by yy642. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_rte_wnli_10_en_5.5.0_3.0_1727413192175.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_rte_wnli_10_en_5.5.0_3.0_1727413192175.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_base_uncased_finetuned_mnli_rte_wnli_10","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mnli_rte_wnli_10", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_rte_wnli_10| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-rte-wnli-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline_en.md new file mode 100644 index 00000000000000..83ba54672fdd73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline pipeline BertForSequenceClassification from yy642 +author: John Snow Labs +name: bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline` is a English model originally trained by yy642. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline_en_5.5.0_3.0_1727413213289.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline_en_5.5.0_3.0_1727413213289.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mnli_rte_wnli_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yy642/bert-base-uncased-finetuned-mnli-rte-wnli-10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_qqp_senfu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_qqp_senfu_pipeline_en.md new file mode 100644 index 00000000000000..45a0b3149550e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_qqp_senfu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_qqp_senfu_pipeline pipeline BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_finetuned_qqp_senfu_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_qqp_senfu_pipeline` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_qqp_senfu_pipeline_en_5.5.0_3.0_1727400632549.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_qqp_senfu_pipeline_en_5.5.0_3.0_1727400632549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_qqp_senfu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_qqp_senfu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_qqp_senfu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-finetuned-qqp + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_rte_minseok0809_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_rte_minseok0809_en.md new file mode 100644 index 00000000000000..adae7697a47946 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_rte_minseok0809_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_rte_minseok0809 BertForSequenceClassification from minseok0809 +author: John Snow Labs +name: bert_base_uncased_finetuned_rte_minseok0809 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_minseok0809` is a English model originally trained by minseok0809. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_minseok0809_en_5.5.0_3.0_1727411358745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_minseok0809_en_5.5.0_3.0_1727411358745.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_base_uncased_finetuned_rte_minseok0809","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_rte_minseok0809", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_rte_minseok0809| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/minseok0809/bert-base-uncased-finetuned-rte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_rte_minseok0809_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_rte_minseok0809_pipeline_en.md new file mode 100644 index 00000000000000..6846b5d3003ff2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_rte_minseok0809_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_rte_minseok0809_pipeline pipeline BertForSequenceClassification from minseok0809 +author: John Snow Labs +name: bert_base_uncased_finetuned_rte_minseok0809_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_rte_minseok0809_pipeline` is a English model originally trained by minseok0809. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_minseok0809_pipeline_en_5.5.0_3.0_1727411390601.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_minseok0809_pipeline_en_5.5.0_3.0_1727411390601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_rte_minseok0809_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_rte_minseok0809_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_rte_minseok0809_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/minseok0809/bert-base-uncased-finetuned-rte + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_w05230505_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_w05230505_en.md new file mode 100644 index 00000000000000..175d0ef8224bf5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_w05230505_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sst2_w05230505 BertForSequenceClassification from w05230505 +author: John Snow Labs +name: bert_base_uncased_finetuned_sst2_w05230505 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sst2_w05230505` is a English model originally trained by w05230505. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_w05230505_en_5.5.0_3.0_1727404451422.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_w05230505_en_5.5.0_3.0_1727404451422.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_base_uncased_finetuned_sst2_w05230505","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sst2_w05230505", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sst2_w05230505| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/w05230505/bert-base-uncased-finetuned-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_xuyi499307483_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_xuyi499307483_en.md new file mode 100644 index 00000000000000..6e26dd508a43eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_xuyi499307483_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sst2_xuyi499307483 BertForSequenceClassification from xuyi499307483 +author: John Snow Labs +name: bert_base_uncased_finetuned_sst2_xuyi499307483 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sst2_xuyi499307483` is a English model originally trained by xuyi499307483. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_xuyi499307483_en_5.5.0_3.0_1727414213667.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_xuyi499307483_en_5.5.0_3.0_1727414213667.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_base_uncased_finetuned_sst2_xuyi499307483","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sst2_xuyi499307483", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sst2_xuyi499307483| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/xuyi499307483/bert-base-uncased-finetuned-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline_en.md new file mode 100644 index 00000000000000..754e4b69c2eeee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline pipeline BertForSequenceClassification from xuyi499307483 +author: John Snow Labs +name: bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline` is a English model originally trained by xuyi499307483. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline_en_5.5.0_3.0_1727414238817.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline_en_5.5.0_3.0_1727414238817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sst2_xuyi499307483_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/xuyi499307483/bert-base-uncased-finetuned-sst2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_stationary_update_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_stationary_update_pipeline_en.md new file mode 100644 index 00000000000000..be06bc15ce6bc8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_stationary_update_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_stationary_update_pipeline pipeline BertForSequenceClassification from MKS3099 +author: John Snow Labs +name: bert_base_uncased_finetuned_stationary_update_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_stationary_update_pipeline` is a English model originally trained by MKS3099. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_stationary_update_pipeline_en_5.5.0_3.0_1727403668242.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_stationary_update_pipeline_en_5.5.0_3.0_1727403668242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_stationary_update_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_stationary_update_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_stationary_update_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MKS3099/bert-base-uncased-finetuned-stationary-update + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sufficiency_dagstuhl_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sufficiency_dagstuhl_en.md new file mode 100644 index 00000000000000..36b23194ef109d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_sufficiency_dagstuhl_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sufficiency_dagstuhl BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_finetuned_sufficiency_dagstuhl +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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` 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_en_5.5.0_3.0_1727419464683.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_en_5.5.0_3.0_1727419464683.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_base_uncased_finetuned_sufficiency_dagstuhl","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_dagstuhl", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sufficiency_dagstuhl| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-finetuned-sufficiency-dagstuhl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_t_refund_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_t_refund_en.md new file mode 100644 index 00000000000000..06bf83467628b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_t_refund_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_t_refund BertForSequenceClassification from Gregorig +author: John Snow Labs +name: bert_base_uncased_finetuned_t_refund +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_t_refund` is a English model originally trained by Gregorig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_t_refund_en_5.5.0_3.0_1727406242917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_t_refund_en_5.5.0_3.0_1727406242917.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_base_uncased_finetuned_t_refund","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_t_refund", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_t_refund| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Gregorig/bert-base-uncased-finetuned-t_refund \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_t_refund_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_t_refund_pipeline_en.md new file mode 100644 index 00000000000000..e684b068a4b2d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_t_refund_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_t_refund_pipeline pipeline BertForSequenceClassification from Gregorig +author: John Snow Labs +name: bert_base_uncased_finetuned_t_refund_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_t_refund_pipeline` is a English model originally trained by Gregorig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_t_refund_pipeline_en_5.5.0_3.0_1727406264102.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_t_refund_pipeline_en_5.5.0_3.0_1727406264102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_t_refund_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_t_refund_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_t_refund_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Gregorig/bert-base-uncased-finetuned-t_refund + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_toxic_comments_detection_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_toxic_comments_detection_en.md new file mode 100644 index 00000000000000..843dd3c3972a5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_finetuned_toxic_comments_detection_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_toxic_comments_detection BertForSequenceClassification from tillschwoerer +author: John Snow Labs +name: bert_base_uncased_finetuned_toxic_comments_detection +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_toxic_comments_detection` is a English model originally trained by tillschwoerer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_toxic_comments_detection_en_5.5.0_3.0_1727419238959.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_toxic_comments_detection_en_5.5.0_3.0_1727419238959.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_base_uncased_finetuned_toxic_comments_detection","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_toxic_comments_detection", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_toxic_comments_detection| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tillschwoerer/bert-base-uncased-finetuned-toxic-comments-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ft_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ft_imdb_pipeline_en.md new file mode 100644 index 00000000000000..4a7c6f39405ee5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ft_imdb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_ft_imdb_pipeline pipeline BertForSequenceClassification from MatFil99 +author: John Snow Labs +name: bert_base_uncased_ft_imdb_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ft_imdb_pipeline` is a English model originally trained by MatFil99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ft_imdb_pipeline_en_5.5.0_3.0_1727412592556.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ft_imdb_pipeline_en_5.5.0_3.0_1727412592556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_ft_imdb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_ft_imdb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ft_imdb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MatFil99/bert-base-uncased-ft-imdb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_header_content_textsim_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_header_content_textsim_en.md new file mode 100644 index 00000000000000..dda3592d6c01c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_header_content_textsim_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_header_content_textsim BertForSequenceClassification from kaanakdeniz +author: John Snow Labs +name: bert_base_uncased_header_content_textsim +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_header_content_textsim` is a English model originally trained by kaanakdeniz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_header_content_textsim_en_5.5.0_3.0_1727419052566.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_header_content_textsim_en_5.5.0_3.0_1727419052566.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_base_uncased_header_content_textsim","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_header_content_textsim", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_header_content_textsim| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kaanakdeniz/bert_base_uncased_header_content_textsim \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_header_content_zeroshot_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_header_content_zeroshot_pipeline_en.md new file mode 100644 index 00000000000000..6f2b6ea3346861 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_header_content_zeroshot_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_header_content_zeroshot_pipeline pipeline BertForSequenceClassification from kaanakdeniz +author: John Snow Labs +name: bert_base_uncased_header_content_zeroshot_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_header_content_zeroshot_pipeline` is a English model originally trained by kaanakdeniz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_header_content_zeroshot_pipeline_en_5.5.0_3.0_1727414893149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_header_content_zeroshot_pipeline_en_5.5.0_3.0_1727414893149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_header_content_zeroshot_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_header_content_zeroshot_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_header_content_zeroshot_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kaanakdeniz/bert_base_uncased_header_content_zeroshot + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm_en.md new file mode 100644 index 00000000000000..aa4f6232f99b34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ibm_argq_30k_finetuned_convincingness_ibm` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm_en_5.5.0_3.0_1727416644073.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm_en_5.5.0_3.0_1727416644073.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_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ibm_argq_30k_finetuned_convincingness_ibm| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-IBM \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv_en.md new file mode 100644 index 00000000000000..a1f67b479e0752 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ibm_argq_30k_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_ibm_argq_30k_finetuned_effectiveness_redditcmv_en_5.5.0_3.0_1727418854234.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv_en_5.5.0_3.0_1727418854234.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_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ibm_argq_30k_finetuned_effectiveness_redditcmv| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-IBM-argQ-30k-finetuned-effectiveness-redditCMV \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_italian_service_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_italian_service_classification_en.md new file mode 100644 index 00000000000000..b6b32c6f374064 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_italian_service_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_italian_service_classification BertForSequenceClassification from kkngan +author: John Snow Labs +name: bert_base_uncased_italian_service_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_italian_service_classification` is a English model originally trained by kkngan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_italian_service_classification_en_5.5.0_3.0_1727416407492.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_italian_service_classification_en_5.5.0_3.0_1727416407492.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_base_uncased_italian_service_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_italian_service_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_italian_service_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/kkngan/bert-base-uncased-it-service-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_jy_survey_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_jy_survey_pipeline_en.md new file mode 100644 index 00000000000000..8468d9668b0ab1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_jy_survey_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_jy_survey_pipeline pipeline BertForSequenceClassification from chanchongwei +author: John Snow Labs +name: bert_base_uncased_jy_survey_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_jy_survey_pipeline` is a English model originally trained by chanchongwei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_jy_survey_pipeline_en_5.5.0_3.0_1727402477876.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_jy_survey_pipeline_en_5.5.0_3.0_1727402477876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_jy_survey_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_jy_survey_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_jy_survey_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/chanchongwei/bert-base-uncased-JY_Survey + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_llm_detect_ai_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_llm_detect_ai_en.md new file mode 100644 index 00000000000000..7def296b6203b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_llm_detect_ai_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_llm_detect_ai BertForSequenceClassification from eljanmahammadli +author: John Snow Labs +name: bert_base_uncased_llm_detect_ai +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_llm_detect_ai` is a English model originally trained by eljanmahammadli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_llm_detect_ai_en_5.5.0_3.0_1727403998685.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_llm_detect_ai_en_5.5.0_3.0_1727403998685.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_base_uncased_llm_detect_ai","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_llm_detect_ai", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_llm_detect_ai| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/eljanmahammadli/bert-base-uncased-llm-detect-ai \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_llm_detect_ai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_llm_detect_ai_pipeline_en.md new file mode 100644 index 00000000000000..ffebaf6609948d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_llm_detect_ai_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_llm_detect_ai_pipeline pipeline BertForSequenceClassification from eljanmahammadli +author: John Snow Labs +name: bert_base_uncased_llm_detect_ai_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_llm_detect_ai_pipeline` is a English model originally trained by eljanmahammadli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_llm_detect_ai_pipeline_en_5.5.0_3.0_1727404023118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_llm_detect_ai_pipeline_en_5.5.0_3.0_1727404023118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_llm_detect_ai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_llm_detect_ai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_llm_detect_ai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/eljanmahammadli/bert-base-uncased-llm-detect-ai + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_mahmoud8_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_mahmoud8_en.md new file mode 100644 index 00000000000000..7994d1c1be7f45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_mahmoud8_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_mahmoud8 BertForSequenceClassification from Mahmoud8 +author: John Snow Labs +name: bert_base_uncased_mahmoud8 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_mahmoud8` is a English model originally trained by Mahmoud8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mahmoud8_en_5.5.0_3.0_1727402855748.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mahmoud8_en_5.5.0_3.0_1727402855748.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_base_uncased_mahmoud8","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mahmoud8", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mahmoud8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Mahmoud8/bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_mrpc_alex_atelo_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_mrpc_alex_atelo_en.md new file mode 100644 index 00000000000000..a9ab123d0e3878 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_mrpc_alex_atelo_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_mrpc_alex_atelo BertForSequenceClassification from alex-atelo +author: John Snow Labs +name: bert_base_uncased_mrpc_alex_atelo +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_alex_atelo` is a English model originally trained by alex-atelo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mrpc_alex_atelo_en_5.5.0_3.0_1727403307712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mrpc_alex_atelo_en_5.5.0_3.0_1727403307712.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_base_uncased_mrpc_alex_atelo","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mrpc_alex_atelo", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mrpc_alex_atelo| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/alex-atelo/bert-base-uncased-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sentiment_portuguese_1_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sentiment_portuguese_1_pipeline_pt.md new file mode 100644 index 00000000000000..785a7dd83f68e7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sentiment_portuguese_1_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese bert_base_uncased_sentiment_portuguese_1_pipeline pipeline BertForSequenceClassification from PamelaBorelli +author: John Snow Labs +name: bert_base_uncased_sentiment_portuguese_1_pipeline +date: 2024-09-27 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sentiment_portuguese_1_pipeline` is a Portuguese model originally trained by PamelaBorelli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sentiment_portuguese_1_pipeline_pt_5.5.0_3.0_1727406156242.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sentiment_portuguese_1_pipeline_pt_5.5.0_3.0_1727406156242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_sentiment_portuguese_1_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_sentiment_portuguese_1_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sentiment_portuguese_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|208.4 MB| + +## References + +https://huggingface.co/PamelaBorelli/bert-base-uncased-sentiment-pt-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sentiment_portuguese_1_pt.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sentiment_portuguese_1_pt.md new file mode 100644 index 00000000000000..c0fc54efa6bf31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sentiment_portuguese_1_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese bert_base_uncased_sentiment_portuguese_1 BertForSequenceClassification from PamelaBorelli +author: John Snow Labs +name: bert_base_uncased_sentiment_portuguese_1 +date: 2024-09-27 +tags: [pt, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sentiment_portuguese_1` is a Portuguese model originally trained by PamelaBorelli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sentiment_portuguese_1_pt_5.5.0_3.0_1727406086253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sentiment_portuguese_1_pt_5.5.0_3.0_1727406086253.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_base_uncased_sentiment_portuguese_1","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sentiment_portuguese_1", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sentiment_portuguese_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|208.4 MB| + +## References + +https://huggingface.co/PamelaBorelli/bert-base-uncased-sentiment-pt-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sst2_distilled_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sst2_distilled_en.md new file mode 100644 index 00000000000000..e5642bdf9a1c06 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_sst2_distilled_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_sst2_distilled BertForSequenceClassification from doyoungkim +author: John Snow Labs +name: bert_base_uncased_sst2_distilled +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_distilled` is a English model originally trained by doyoungkim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_distilled_en_5.5.0_3.0_1727416221108.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_distilled_en_5.5.0_3.0_1727416221108.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_base_uncased_sst2_distilled","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst2_distilled", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst2_distilled| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/doyoungkim/bert-base-uncased-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_from_bert_large_uncased_stsb_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_from_bert_large_uncased_stsb_en.md new file mode 100644 index 00000000000000..bc91af97db83f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_from_bert_large_uncased_stsb_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_stsb_from_bert_large_uncased_stsb BertForSequenceClassification from yoshitomo-matsubara +author: John Snow Labs +name: bert_base_uncased_stsb_from_bert_large_uncased_stsb +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_from_bert_large_uncased_stsb` is a English model originally trained by yoshitomo-matsubara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_from_bert_large_uncased_stsb_en_5.5.0_3.0_1727403022053.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_from_bert_large_uncased_stsb_en_5.5.0_3.0_1727403022053.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_base_uncased_stsb_from_bert_large_uncased_stsb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stsb_from_bert_large_uncased_stsb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_stsb_from_bert_large_uncased_stsb| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yoshitomo-matsubara/bert-base-uncased-stsb_from_bert-large-uncased-stsb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_howey_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_howey_en.md new file mode 100644 index 00000000000000..e96ef4533b3b23 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_howey_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_stsb_howey BertForSequenceClassification from howey +author: John Snow Labs +name: bert_base_uncased_stsb_howey +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_howey` is a English model originally trained by howey. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_howey_en_5.5.0_3.0_1727401222852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_howey_en_5.5.0_3.0_1727401222852.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_base_uncased_stsb_howey","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stsb_howey", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_stsb_howey| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/howey/bert-base-uncased-stsb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_howey_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_howey_pipeline_en.md new file mode 100644 index 00000000000000..6da9c9473cc3a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_howey_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_stsb_howey_pipeline pipeline BertForSequenceClassification from howey +author: John Snow Labs +name: bert_base_uncased_stsb_howey_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_stsb_howey_pipeline` is a English model originally trained by howey. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_howey_pipeline_en_5.5.0_3.0_1727401245116.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_howey_pipeline_en_5.5.0_3.0_1727401245116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_stsb_howey_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_stsb_howey_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_stsb_howey_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/howey/bert-base-uncased-stsb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_modeltc_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_modeltc_pipeline_en.md new file mode 100644 index 00000000000000..f62fb99872e615 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_stsb_modeltc_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_stsb_modeltc_pipeline pipeline BertForSequenceClassification from ModelTC +author: John Snow Labs +name: bert_base_uncased_stsb_modeltc_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_stsb_modeltc_pipeline` is a English model originally trained by ModelTC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_modeltc_pipeline_en_5.5.0_3.0_1727400605759.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_modeltc_pipeline_en_5.5.0_3.0_1727400605759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_stsb_modeltc_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_stsb_modeltc_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_stsb_modeltc_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ModelTC/bert-base-uncased-stsb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_textcls_rheology_20230912_2_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_textcls_rheology_20230912_2_en.md new file mode 100644 index 00000000000000..152d2eaca1c486 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_textcls_rheology_20230912_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_textcls_rheology_20230912_2 BertForSequenceClassification from jonas-luehrs +author: John Snow Labs +name: bert_base_uncased_textcls_rheology_20230912_2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_textcls_rheology_20230912_2` is a English model originally trained by jonas-luehrs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_textcls_rheology_20230912_2_en_5.5.0_3.0_1727402885722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_textcls_rheology_20230912_2_en_5.5.0_3.0_1727402885722.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_base_uncased_textcls_rheology_20230912_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_textcls_rheology_20230912_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_textcls_rheology_20230912_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jonas-luehrs/bert-base-uncased-textCLS-RHEOLOGY-20230912-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_mnli_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_mnli_en.md new file mode 100644 index 00000000000000..eee783ababf229 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_mnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_top_pruned_mnli BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_top_pruned_mnli +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_top_pruned_mnli` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_top_pruned_mnli_en_5.5.0_3.0_1727417667379.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_top_pruned_mnli_en_5.5.0_3.0_1727417667379.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_base_uncased_top_pruned_mnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_top_pruned_mnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_top_pruned_mnli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-top-pruned-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_qnli_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_qnli_en.md new file mode 100644 index 00000000000000..a84fde31aa0134 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_qnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_top_pruned_qnli BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_top_pruned_qnli +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_top_pruned_qnli` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_top_pruned_qnli_en_5.5.0_3.0_1727416811732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_top_pruned_qnli_en_5.5.0_3.0_1727416811732.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_base_uncased_top_pruned_qnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_top_pruned_qnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_top_pruned_qnli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-top-pruned-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_qnli_pipeline_en.md new file mode 100644 index 00000000000000..75671f75b71077 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_top_pruned_qnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_top_pruned_qnli_pipeline pipeline BertForSequenceClassification from senfu +author: John Snow Labs +name: bert_base_uncased_top_pruned_qnli_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_top_pruned_qnli_pipeline` is a English model originally trained by senfu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_top_pruned_qnli_pipeline_en_5.5.0_3.0_1727416832722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_top_pruned_qnli_pipeline_en_5.5.0_3.0_1727416832722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_top_pruned_qnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_top_pruned_qnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_top_pruned_qnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/senfu/bert-base-uncased-top-pruned-qnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline_en.md new file mode 100644 index 00000000000000..0c8371be7e5364 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline pipeline BertForSequenceClassification from Ioanaaaaaaa +author: John Snow Labs +name: bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline` is a English model originally trained by Ioanaaaaaaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline_en_5.5.0_3.0_1727414519889.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline_en_5.5.0_3.0_1727414519889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_0_1_weight_decay_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ioanaaaaaaa/bert-base-uncased-with-preprocess-finetuned-emotion-5-epochs-5e-05-lr-0.1-weight_decay + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_year_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_year_classifier_en.md new file mode 100644 index 00000000000000..5c31324ac4808d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_year_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_year_classifier BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_year_classifier +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_year_classifier` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_year_classifier_en_5.5.0_3.0_1727413872916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_year_classifier_en_5.5.0_3.0_1727413872916.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_base_year_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_year_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_year_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/research-dump/bert_base_year_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_base_year_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_base_year_classifier_pipeline_en.md new file mode 100644 index 00000000000000..70bd0503677448 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_base_year_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_year_classifier_pipeline pipeline BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_year_classifier_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_year_classifier_pipeline` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_year_classifier_pipeline_en_5.5.0_3.0_1727413893682.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_year_classifier_pipeline_en_5.5.0_3.0_1727413893682.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_year_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_year_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_year_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/research-dump/bert_base_year_classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_based_uncased_finetuned_financial_talk_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_based_uncased_finetuned_financial_talk_pipeline_en.md new file mode 100644 index 00000000000000..ecacc15d1b2f51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_based_uncased_finetuned_financial_talk_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_based_uncased_finetuned_financial_talk_pipeline pipeline BertForSequenceClassification from odunola +author: John Snow Labs +name: bert_based_uncased_finetuned_financial_talk_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_based_uncased_finetuned_financial_talk_pipeline` is a English model originally trained by odunola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_based_uncased_finetuned_financial_talk_pipeline_en_5.5.0_3.0_1727401563527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_based_uncased_finetuned_financial_talk_pipeline_en_5.5.0_3.0_1727401563527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_based_uncased_finetuned_financial_talk_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_based_uncased_finetuned_financial_talk_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_based_uncased_finetuned_financial_talk_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/odunola/bert-based_uncased-finetuned-financial-talk + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_clean_semaphore_prediction_w8_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_clean_semaphore_prediction_w8_en.md new file mode 100644 index 00000000000000..7b00c2d0a6f46c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_clean_semaphore_prediction_w8_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_clean_semaphore_prediction_w8 BertForSequenceClassification from bondi +author: John Snow Labs +name: bert_clean_semaphore_prediction_w8 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_clean_semaphore_prediction_w8` is a English model originally trained by bondi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_clean_semaphore_prediction_w8_en_5.5.0_3.0_1727410254652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_clean_semaphore_prediction_w8_en_5.5.0_3.0_1727410254652.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_clean_semaphore_prediction_w8","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_clean_semaphore_prediction_w8", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_clean_semaphore_prediction_w8| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/bondi/bert-clean-semaphore-prediction-w8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_clean_semaphore_prediction_w8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_clean_semaphore_prediction_w8_pipeline_en.md new file mode 100644 index 00000000000000..bafae85b1a94d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_clean_semaphore_prediction_w8_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_clean_semaphore_prediction_w8_pipeline pipeline BertForSequenceClassification from bondi +author: John Snow Labs +name: bert_clean_semaphore_prediction_w8_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_clean_semaphore_prediction_w8_pipeline` is a English model originally trained by bondi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_clean_semaphore_prediction_w8_pipeline_en_5.5.0_3.0_1727410275355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_clean_semaphore_prediction_w8_pipeline_en_5.5.0_3.0_1727410275355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_clean_semaphore_prediction_w8_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_clean_semaphore_prediction_w8_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_clean_semaphore_prediction_w8_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/bondi/bert-clean-semaphore-prediction-w8 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_qingtan007_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_qingtan007_en.md new file mode 100644 index 00000000000000..89d5a18264cccd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_qingtan007_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_cn_finetuning_qingtan007 BertForSequenceClassification from qingtan007 +author: John Snow Labs +name: bert_cn_finetuning_qingtan007 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_qingtan007` is a English model originally trained by qingtan007. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_qingtan007_en_5.5.0_3.0_1727408926659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_qingtan007_en_5.5.0_3.0_1727408926659.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_cn_finetuning_qingtan007","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_qingtan007", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetuning_qingtan007| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/qingtan007/bert_cn_finetuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_qingtan007_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_qingtan007_pipeline_en.md new file mode 100644 index 00000000000000..7ae10b157a8e90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_qingtan007_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_cn_finetuning_qingtan007_pipeline pipeline BertForSequenceClassification from qingtan007 +author: John Snow Labs +name: bert_cn_finetuning_qingtan007_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cn_finetuning_qingtan007_pipeline` is a English model originally trained by qingtan007. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_qingtan007_pipeline_en_5.5.0_3.0_1727408949191.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_qingtan007_pipeline_en_5.5.0_3.0_1727408949191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_cn_finetuning_qingtan007_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_cn_finetuning_qingtan007_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetuning_qingtan007_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/qingtan007/bert_cn_finetuning + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_song_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_song_en.md new file mode 100644 index 00000000000000..24159182b025f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_cn_finetuning_song_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_cn_finetuning_song BertForSequenceClassification from song +author: John Snow Labs +name: bert_cn_finetuning_song +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_song` is a English model originally trained by song. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_song_en_5.5.0_3.0_1727409810180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_song_en_5.5.0_3.0_1727409810180.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_cn_finetuning_song","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_song", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetuning_song| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/song/bert_cn_finetuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_financial_sentiment_analysis_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_financial_sentiment_analysis_en.md new file mode 100644 index 00000000000000..a28fa1b3916b2f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_financial_sentiment_analysis_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_financial_sentiment_analysis BertForSequenceClassification from carloszansavio +author: John Snow Labs +name: bert_financial_sentiment_analysis +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_financial_sentiment_analysis` is a English model originally trained by carloszansavio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_financial_sentiment_analysis_en_5.5.0_3.0_1727404534237.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_financial_sentiment_analysis_en_5.5.0_3.0_1727404534237.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_financial_sentiment_analysis","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_financial_sentiment_analysis", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_financial_sentiment_analysis| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/carloszansavio/bert-financial-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_financial_sentiment_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_financial_sentiment_analysis_pipeline_en.md new file mode 100644 index 00000000000000..3dcc2670221973 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_financial_sentiment_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_financial_sentiment_analysis_pipeline pipeline BertForSequenceClassification from carloszansavio +author: John Snow Labs +name: bert_financial_sentiment_analysis_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_financial_sentiment_analysis_pipeline` is a English model originally trained by carloszansavio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_financial_sentiment_analysis_pipeline_en_5.5.0_3.0_1727404554701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_financial_sentiment_analysis_pipeline_en_5.5.0_3.0_1727404554701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_financial_sentiment_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_financial_sentiment_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_financial_sentiment_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/carloszansavio/bert-financial-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_cola_khaledai_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_cola_khaledai_en.md new file mode 100644 index 00000000000000..d7cd99a530f397 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_cola_khaledai_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_fine_tuned_cola_khaledai BertForSequenceClassification from Khaledai +author: John Snow Labs +name: bert_fine_tuned_cola_khaledai +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_khaledai` is a English model originally trained by Khaledai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_khaledai_en_5.5.0_3.0_1727413736771.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_khaledai_en_5.5.0_3.0_1727413736771.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_fine_tuned_cola_khaledai","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_khaledai", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_cola_khaledai| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Khaledai/bert-fine-tuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_cola_khaledai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_cola_khaledai_pipeline_en.md new file mode 100644 index 00000000000000..52ec29617cfbe6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_cola_khaledai_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_fine_tuned_cola_khaledai_pipeline pipeline BertForSequenceClassification from Khaledai +author: John Snow Labs +name: bert_fine_tuned_cola_khaledai_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_cola_khaledai_pipeline` is a English model originally trained by Khaledai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_khaledai_pipeline_en_5.5.0_3.0_1727413758278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_khaledai_pipeline_en_5.5.0_3.0_1727413758278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_fine_tuned_cola_khaledai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_fine_tuned_cola_khaledai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_cola_khaledai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Khaledai/bert-fine-tuned-cola + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_wic_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_wic_en.md new file mode 100644 index 00000000000000..56068cc43c97b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_wic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_fine_tuned_wic BertForSequenceClassification from rycecorn +author: John Snow Labs +name: bert_fine_tuned_wic +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_wic` is a English model originally trained by rycecorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_wic_en_5.5.0_3.0_1727395769994.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_wic_en_5.5.0_3.0_1727395769994.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_fine_tuned_wic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_wic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_wic| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rycecorn/Bert-fine-tuned-WiC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_wic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_wic_pipeline_en.md new file mode 100644 index 00000000000000..2fddcb60016aa3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_fine_tuned_wic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_fine_tuned_wic_pipeline pipeline BertForSequenceClassification from rycecorn +author: John Snow Labs +name: bert_fine_tuned_wic_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_wic_pipeline` is a English model originally trained by rycecorn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_wic_pipeline_en_5.5.0_3.0_1727395790862.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_wic_pipeline_en_5.5.0_3.0_1727395790862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_fine_tuned_wic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_fine_tuned_wic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_wic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rycecorn/Bert-fine-tuned-WiC + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_locations_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_locations_en.md new file mode 100644 index 00000000000000..1a7a9fdcd519e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_locations_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_locations BertForSequenceClassification from dendimaki +author: John Snow Labs +name: bert_finetuned_locations +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_locations` is a English model originally trained by dendimaki. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_locations_en_5.5.0_3.0_1727404416450.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_locations_en_5.5.0_3.0_1727404416450.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_finetuned_locations","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_locations", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_locations| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/dendimaki/bert-finetuned-locations \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline_en.md new file mode 100644 index 00000000000000..df3bc19341cb43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline pipeline BertForSequenceClassification from rajivkale +author: John Snow Labs +name: bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline` is a English model originally trained by rajivkale. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline_en_5.5.0_3.0_1727408852931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline_en_5.5.0_3.0_1727408852931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_semitic_languages_eval_english_rajivkale_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rajivkale/bert-finetuned-sem_eval-english + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_semitic_languages_eval_rest14_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_semitic_languages_eval_rest14_english_pipeline_en.md new file mode 100644 index 00000000000000..7d6019603f2e6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_finetuned_semitic_languages_eval_rest14_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_semitic_languages_eval_rest14_english_pipeline pipeline BertForSequenceClassification from car13mesquita +author: John Snow Labs +name: bert_finetuned_semitic_languages_eval_rest14_english_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_semitic_languages_eval_rest14_english_pipeline` is a English model originally trained by car13mesquita. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_semitic_languages_eval_rest14_english_pipeline_en_5.5.0_3.0_1727407532515.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_semitic_languages_eval_rest14_english_pipeline_en_5.5.0_3.0_1727407532515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_semitic_languages_eval_rest14_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_semitic_languages_eval_rest14_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_semitic_languages_eval_rest14_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/car13mesquita/bert-finetuned-sem_eval-rest14-english + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_kan_rom_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_kan_rom_en.md new file mode 100644 index 00000000000000..f2c6a6ff6d4f0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_kan_rom_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_kan_rom BertForSequenceClassification from reevan +author: John Snow Labs +name: bert_kan_rom +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_kan_rom` is a English model originally trained by reevan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_kan_rom_en_5.5.0_3.0_1727413783034.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_kan_rom_en_5.5.0_3.0_1727413783034.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_kan_rom","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_kan_rom", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_kan_rom| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/reevan/bert_kan_rom \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_kan_rom_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_kan_rom_pipeline_en.md new file mode 100644 index 00000000000000..17ca0e10a4fefd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_kan_rom_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_kan_rom_pipeline pipeline BertForSequenceClassification from reevan +author: John Snow Labs +name: bert_kan_rom_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_kan_rom_pipeline` is a English model originally trained by reevan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_kan_rom_pipeline_en_5.5.0_3.0_1727413813823.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_kan_rom_pipeline_en_5.5.0_3.0_1727413813823.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_kan_rom_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_kan_rom_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_kan_rom_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/reevan/bert_kan_rom + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_categorization_uncased_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_categorization_uncased_finetuned_en.md new file mode 100644 index 00000000000000..c2b5e3029af9a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_categorization_uncased_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_categorization_uncased_finetuned BertForSequenceClassification from kranasian +author: John Snow Labs +name: bert_large_categorization_uncased_finetuned +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_categorization_uncased_finetuned` is a English model originally trained by kranasian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_categorization_uncased_finetuned_en_5.5.0_3.0_1727407723905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_categorization_uncased_finetuned_en_5.5.0_3.0_1727407723905.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_large_categorization_uncased_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_categorization_uncased_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_categorization_uncased_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/kranasian/bert-large-categorization-uncased-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_categorization_uncased_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_categorization_uncased_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..4b3aa1cdd3a05e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_categorization_uncased_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_categorization_uncased_finetuned_pipeline pipeline BertForSequenceClassification from kranasian +author: John Snow Labs +name: bert_large_categorization_uncased_finetuned_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_categorization_uncased_finetuned_pipeline` is a English model originally trained by kranasian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_categorization_uncased_finetuned_pipeline_en_5.5.0_3.0_1727407785271.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_categorization_uncased_finetuned_pipeline_en_5.5.0_3.0_1727407785271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_categorization_uncased_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_categorization_uncased_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_categorization_uncased_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/kranasian/bert-large-categorization-uncased-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_e2_version2_noweight_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_e2_version2_noweight_en.md new file mode 100644 index 00000000000000..b897d4aa1d86f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_e2_version2_noweight_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_e2_version2_noweight BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: bert_large_e2_version2_noweight +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_e2_version2_noweight` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_e2_version2_noweight_en_5.5.0_3.0_1727408916325.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_e2_version2_noweight_en_5.5.0_3.0_1727408916325.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_large_e2_version2_noweight","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_e2_version2_noweight", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_e2_version2_noweight| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/bert-large-e2-version2-noweight \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_finetuned_phishing_url_version_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_finetuned_phishing_url_version_en.md new file mode 100644 index 00000000000000..f1c1f426628fb0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_finetuned_phishing_url_version_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_finetuned_phishing_url_version BertForSequenceClassification from huynq3Cyradar +author: John Snow Labs +name: bert_large_finetuned_phishing_url_version +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_finetuned_phishing_url_version` is a English model originally trained by huynq3Cyradar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_url_version_en_5.5.0_3.0_1727398589405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_url_version_en_5.5.0_3.0_1727398589405.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_large_finetuned_phishing_url_version","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_finetuned_phishing_url_version", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_finetuned_phishing_url_version| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/huynq3Cyradar/bert-large-finetuned-phishing-url-version \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_cased_faquad_nli_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_cased_faquad_nli_pipeline_pt.md new file mode 100644 index 00000000000000..455e6dc4bef954 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_cased_faquad_nli_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese bert_large_portuguese_cased_faquad_nli_pipeline pipeline BertForSequenceClassification from ruanchaves +author: John Snow Labs +name: bert_large_portuguese_cased_faquad_nli_pipeline +date: 2024-09-27 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_portuguese_cased_faquad_nli_pipeline` is a Portuguese model originally trained by ruanchaves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_cased_faquad_nli_pipeline_pt_5.5.0_3.0_1727396614560.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_cased_faquad_nli_pipeline_pt_5.5.0_3.0_1727396614560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_portuguese_cased_faquad_nli_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_portuguese_cased_faquad_nli_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_portuguese_cased_faquad_nli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ruanchaves/bert-large-portuguese-cased-faquad-nli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_cased_faquad_nli_pt.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_cased_faquad_nli_pt.md new file mode 100644 index 00000000000000..d424b42ca02a31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_cased_faquad_nli_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese bert_large_portuguese_cased_faquad_nli BertForSequenceClassification from ruanchaves +author: John Snow Labs +name: bert_large_portuguese_cased_faquad_nli +date: 2024-09-27 +tags: [pt, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_portuguese_cased_faquad_nli` is a Portuguese model originally trained by ruanchaves. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_cased_faquad_nli_pt_5.5.0_3.0_1727396548704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_cased_faquad_nli_pt_5.5.0_3.0_1727396548704.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_large_portuguese_cased_faquad_nli","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_portuguese_cased_faquad_nli", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_portuguese_cased_faquad_nli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ruanchaves/bert-large-portuguese-cased-faquad-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_socioambiental_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_socioambiental_en.md new file mode 100644 index 00000000000000..394781d198005e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_portuguese_socioambiental_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_portuguese_socioambiental BertForSequenceClassification from guilhermedrud +author: John Snow Labs +name: bert_large_portuguese_socioambiental +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_portuguese_socioambiental` is a English model originally trained by guilhermedrud. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_socioambiental_en_5.5.0_3.0_1727403611885.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_portuguese_socioambiental_en_5.5.0_3.0_1727403611885.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_large_portuguese_socioambiental","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_portuguese_socioambiental", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_portuguese_socioambiental| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/guilhermedrud/bert-large-portuguese-socioambiental \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_sexism_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_sexism_classifier_en.md new file mode 100644 index 00000000000000..79322a0694b3cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_sexism_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_sexism_classifier BertForSequenceClassification from MatteoWood +author: John Snow Labs +name: bert_large_sexism_classifier +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sexism_classifier` is a English model originally trained by MatteoWood. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_sexism_classifier_en_5.5.0_3.0_1727414291270.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_sexism_classifier_en_5.5.0_3.0_1727414291270.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_large_sexism_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_sexism_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_sexism_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/MatteoWood/bert-large-sexism-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_sexism_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_sexism_classifier_pipeline_en.md new file mode 100644 index 00000000000000..f76fda138570dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_sexism_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_sexism_classifier_pipeline pipeline BertForSequenceClassification from MatteoWood +author: John Snow Labs +name: bert_large_sexism_classifier_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_sexism_classifier_pipeline` is a English model originally trained by MatteoWood. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_sexism_classifier_pipeline_en_5.5.0_3.0_1727414355788.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_sexism_classifier_pipeline_en_5.5.0_3.0_1727414355788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_sexism_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_sexism_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_sexism_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/MatteoWood/bert-large-sexism-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_uncased_iab_categories_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_uncased_iab_categories_classification_en.md new file mode 100644 index 00000000000000..e902654ca6890c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_uncased_iab_categories_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_uncased_iab_categories_classification BertForSequenceClassification from PavanDeepak +author: John Snow Labs +name: bert_large_uncased_iab_categories_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_iab_categories_classification` is a English model originally trained by PavanDeepak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_iab_categories_classification_en_5.5.0_3.0_1727415530835.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_iab_categories_classification_en_5.5.0_3.0_1727415530835.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_large_uncased_iab_categories_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_iab_categories_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_iab_categories_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/PavanDeepak/bert_large_uncased_iab_categories_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_large_uncased_iab_categories_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_large_uncased_iab_categories_classification_pipeline_en.md new file mode 100644 index 00000000000000..985575b5691344 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_large_uncased_iab_categories_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_uncased_iab_categories_classification_pipeline pipeline BertForSequenceClassification from PavanDeepak +author: John Snow Labs +name: bert_large_uncased_iab_categories_classification_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_iab_categories_classification_pipeline` is a English model originally trained by PavanDeepak. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_iab_categories_classification_pipeline_en_5.5.0_3.0_1727415593220.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_iab_categories_classification_pipeline_en_5.5.0_3.0_1727415593220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_uncased_iab_categories_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_uncased_iab_categories_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_iab_categories_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/PavanDeepak/bert_large_uncased_iab_categories_classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_mail_spam_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_mail_spam_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..16a0914a974c96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_mail_spam_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mail_spam_finetuned_pipeline pipeline BertForSequenceClassification from alexsd06 +author: John Snow Labs +name: bert_mail_spam_finetuned_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mail_spam_finetuned_pipeline` is a English model originally trained by alexsd06. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mail_spam_finetuned_pipeline_en_5.5.0_3.0_1727403766772.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mail_spam_finetuned_pipeline_en_5.5.0_3.0_1727403766772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mail_spam_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mail_spam_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mail_spam_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/alexsd06/bert-mail-spam-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_mdgender_wizard_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_mdgender_wizard_en.md new file mode 100644 index 00000000000000..d80542c4b7b0f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_mdgender_wizard_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_mdgender_wizard BertForSequenceClassification from Cameron +author: John Snow Labs +name: bert_mdgender_wizard +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mdgender_wizard` is a English model originally trained by Cameron. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mdgender_wizard_en_5.5.0_3.0_1727401820726.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mdgender_wizard_en_5.5.0_3.0_1727401820726.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_mdgender_wizard","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mdgender_wizard", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mdgender_wizard| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Cameron/BERT-mdgender-wizard \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_mdgender_wizard_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_mdgender_wizard_pipeline_en.md new file mode 100644 index 00000000000000..0b056157409a9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_mdgender_wizard_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mdgender_wizard_pipeline pipeline BertForSequenceClassification from Cameron +author: John Snow Labs +name: bert_mdgender_wizard_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mdgender_wizard_pipeline` is a English model originally trained by Cameron. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mdgender_wizard_pipeline_en_5.5.0_3.0_1727401841321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mdgender_wizard_pipeline_en_5.5.0_3.0_1727401841321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mdgender_wizard_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mdgender_wizard_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mdgender_wizard_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Cameron/BERT-mdgender-wizard + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_mini_emotion_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_mini_emotion_classifier_pipeline_en.md new file mode 100644 index 00000000000000..a693bc6be7c3db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_mini_emotion_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_mini_emotion_classifier_pipeline pipeline BertForSequenceClassification from gabrielblins +author: John Snow Labs +name: bert_mini_emotion_classifier_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_emotion_classifier_pipeline` is a English model originally trained by gabrielblins. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_emotion_classifier_pipeline_en_5.5.0_3.0_1727409478241.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_emotion_classifier_pipeline_en_5.5.0_3.0_1727409478241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_mini_emotion_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_mini_emotion_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_emotion_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/gabrielblins/bert-mini-emotion_classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_multilabel_tagalog_hate_speech_classifier_pipeline_tl.md b/docs/_posts/ahmedlone127/2024-09-27-bert_multilabel_tagalog_hate_speech_classifier_pipeline_tl.md new file mode 100644 index 00000000000000..62b60a7611445a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_multilabel_tagalog_hate_speech_classifier_pipeline_tl.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Tagalog bert_multilabel_tagalog_hate_speech_classifier_pipeline pipeline BertForSequenceClassification from syke9p3 +author: John Snow Labs +name: bert_multilabel_tagalog_hate_speech_classifier_pipeline +date: 2024-09-27 +tags: [tl, open_source, pipeline, onnx] +task: Text Classification +language: tl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilabel_tagalog_hate_speech_classifier_pipeline` is a Tagalog model originally trained by syke9p3. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilabel_tagalog_hate_speech_classifier_pipeline_tl_5.5.0_3.0_1727397674736.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilabel_tagalog_hate_speech_classifier_pipeline_tl_5.5.0_3.0_1727397674736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_multilabel_tagalog_hate_speech_classifier_pipeline", lang = "tl") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_multilabel_tagalog_hate_speech_classifier_pipeline", lang = "tl") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_multilabel_tagalog_hate_speech_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tl| +|Size:|472.0 MB| + +## References + +https://huggingface.co/syke9p3/bert-multilabel-tagalog-hate-speech-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_multilabel_tagalog_hate_speech_classifier_tl.md b/docs/_posts/ahmedlone127/2024-09-27-bert_multilabel_tagalog_hate_speech_classifier_tl.md new file mode 100644 index 00000000000000..aea71a0bcf1b6f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_multilabel_tagalog_hate_speech_classifier_tl.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Tagalog bert_multilabel_tagalog_hate_speech_classifier BertForSequenceClassification from syke9p3 +author: John Snow Labs +name: bert_multilabel_tagalog_hate_speech_classifier +date: 2024-09-27 +tags: [tl, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: tl +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilabel_tagalog_hate_speech_classifier` is a Tagalog model originally trained by syke9p3. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilabel_tagalog_hate_speech_classifier_tl_5.5.0_3.0_1727397650882.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilabel_tagalog_hate_speech_classifier_tl_5.5.0_3.0_1727397650882.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_multilabel_tagalog_hate_speech_classifier","tl") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilabel_tagalog_hate_speech_classifier", "tl") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_multilabel_tagalog_hate_speech_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|tl| +|Size:|472.0 MB| + +## References + +https://huggingface.co/syke9p3/bert-multilabel-tagalog-hate-speech-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_restaurant_review_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_restaurant_review_en.md new file mode 100644 index 00000000000000..778eb43bb2b2c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_restaurant_review_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_restaurant_review BertForSequenceClassification from vish26 +author: John Snow Labs +name: bert_restaurant_review +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_restaurant_review` is a English model originally trained by vish26. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_restaurant_review_en_5.5.0_3.0_1727403113392.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_restaurant_review_en_5.5.0_3.0_1727403113392.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_restaurant_review","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_restaurant_review", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_restaurant_review| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/vish26/BERT-Restaurant-review \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_restaurant_review_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_restaurant_review_pipeline_en.md new file mode 100644 index 00000000000000..e505a49a6edf12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_restaurant_review_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_restaurant_review_pipeline pipeline BertForSequenceClassification from vish26 +author: John Snow Labs +name: bert_restaurant_review_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_restaurant_review_pipeline` is a English model originally trained by vish26. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_restaurant_review_pipeline_en_5.5.0_3.0_1727403134780.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_restaurant_review_pipeline_en_5.5.0_3.0_1727403134780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_restaurant_review_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_restaurant_review_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_restaurant_review_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/vish26/BERT-Restaurant-review + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_reviews_iiro_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_reviews_iiro_en.md new file mode 100644 index 00000000000000..33a86986c2e91d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_reviews_iiro_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_reviews_iiro BertForSequenceClassification from Iiro +author: John Snow Labs +name: bert_reviews_iiro +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_reviews_iiro` is a English model originally trained by Iiro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_reviews_iiro_en_5.5.0_3.0_1727402692142.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_reviews_iiro_en_5.5.0_3.0_1727402692142.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_reviews_iiro","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_reviews_iiro", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_reviews_iiro| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Iiro/bert_reviews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_reviews_iiro_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_reviews_iiro_pipeline_en.md new file mode 100644 index 00000000000000..f99dcac48aaabd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_reviews_iiro_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_reviews_iiro_pipeline pipeline BertForSequenceClassification from Iiro +author: John Snow Labs +name: bert_reviews_iiro_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_reviews_iiro_pipeline` is a English model originally trained by Iiro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_reviews_iiro_pipeline_en_5.5.0_3.0_1727402713019.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_reviews_iiro_pipeline_en_5.5.0_3.0_1727402713019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_reviews_iiro_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_reviews_iiro_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_reviews_iiro_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Iiro/bert_reviews + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_seq_training_model_multiple_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_seq_training_model_multiple_en.md new file mode 100644 index 00000000000000..6a34fffd657d17 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_seq_training_model_multiple_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_seq_training_model_multiple BertForSequenceClassification from Brecon +author: John Snow Labs +name: bert_seq_training_model_multiple +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_seq_training_model_multiple` is a English model originally trained by Brecon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_seq_training_model_multiple_en_5.5.0_3.0_1727404195513.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_seq_training_model_multiple_en_5.5.0_3.0_1727404195513.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_seq_training_model_multiple","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_seq_training_model_multiple", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_seq_training_model_multiple| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Brecon/bert_seq_training_model_multiple \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_sequence_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_sequence_classification_en.md new file mode 100644 index 00000000000000..54650102d78620 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_sequence_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sequence_classification BertForSequenceClassification from akashmaggon +author: John Snow Labs +name: bert_sequence_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_classification` is a English model originally trained by akashmaggon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classification_en_5.5.0_3.0_1727403859930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classification_en_5.5.0_3.0_1727403859930.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_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/akashmaggon/Bert-sequence-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_sequence_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_sequence_classification_pipeline_en.md new file mode 100644 index 00000000000000..2364df416acf20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_sequence_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sequence_classification_pipeline pipeline BertForSequenceClassification from akashmaggon +author: John Snow Labs +name: bert_sequence_classification_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classification_pipeline` is a English model originally trained by akashmaggon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classification_pipeline_en_5.5.0_3.0_1727403881252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classification_pipeline_en_5.5.0_3.0_1727403881252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sequence_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sequence_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/akashmaggon/Bert-sequence-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_small_uncased_512_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_small_uncased_512_en.md new file mode 100644 index 00000000000000..612e7b2480f2f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_small_uncased_512_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_small_uncased_512 BertForSequenceClassification from autonomous019 +author: John Snow Labs +name: bert_small_uncased_512 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_small_uncased_512` is a English model originally trained by autonomous019. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_small_uncased_512_en_5.5.0_3.0_1727407047433.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_small_uncased_512_en_5.5.0_3.0_1727407047433.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_small_uncased_512","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_small_uncased_512", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_small_uncased_512| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|108.0 MB| + +## References + +https://huggingface.co/autonomous019/bert_small_uncased_512 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_small_uncased_512_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_small_uncased_512_pipeline_en.md new file mode 100644 index 00000000000000..2cfde58ae2b0cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_small_uncased_512_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_small_uncased_512_pipeline pipeline BertForSequenceClassification from autonomous019 +author: John Snow Labs +name: bert_small_uncased_512_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_small_uncased_512_pipeline` is a English model originally trained by autonomous019. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_small_uncased_512_pipeline_en_5.5.0_3.0_1727407052957.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_small_uncased_512_pipeline_en_5.5.0_3.0_1727407052957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_small_uncased_512_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_small_uncased_512_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_small_uncased_512_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|108.0 MB| + +## References + +https://huggingface.co/autonomous019/bert_small_uncased_512 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_sst5_padding30model_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_sst5_padding30model_en.md new file mode 100644 index 00000000000000..d2f3632aefccf1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_sst5_padding30model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_sst5_padding30model BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst5_padding30model +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst5_padding30model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst5_padding30model_en_5.5.0_3.0_1727406339608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst5_padding30model_en_5.5.0_3.0_1727406339608.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_sst5_padding30model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sst5_padding30model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst5_padding30model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst5_padding30model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_sst5_padding30model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_sst5_padding30model_pipeline_en.md new file mode 100644 index 00000000000000..28c572d513878c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_sst5_padding30model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_sst5_padding30model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_sst5_padding30model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sst5_padding30model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sst5_padding30model_pipeline_en_5.5.0_3.0_1727406360176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sst5_padding30model_pipeline_en_5.5.0_3.0_1727406360176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sst5_padding30model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sst5_padding30model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sst5_padding30model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_sst5_padding30model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_tiny_ai_human_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_tiny_ai_human_en.md new file mode 100644 index 00000000000000..85811c528898c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_tiny_ai_human_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_tiny_ai_human BertForSequenceClassification from andythetechnerd03 +author: John Snow Labs +name: bert_tiny_ai_human +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_ai_human` is a English model originally trained by andythetechnerd03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_ai_human_en_5.5.0_3.0_1727419093865.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_ai_human_en_5.5.0_3.0_1727419093865.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_tiny_ai_human","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_ai_human", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_ai_human| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/andythetechnerd03/BERT-tiny_AI-Human \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_tiny_ai_human_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_tiny_ai_human_pipeline_en.md new file mode 100644 index 00000000000000..6ea444268c34e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_tiny_ai_human_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_tiny_ai_human_pipeline pipeline BertForSequenceClassification from andythetechnerd03 +author: John Snow Labs +name: bert_tiny_ai_human_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_ai_human_pipeline` is a English model originally trained by andythetechnerd03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_ai_human_pipeline_en_5.5.0_3.0_1727419095137.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_ai_human_pipeline_en_5.5.0_3.0_1727419095137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_tiny_ai_human_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_tiny_ai_human_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_ai_human_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|16.8 MB| + +## References + +https://huggingface.co/andythetechnerd03/BERT-tiny_AI-Human + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_twitter_spanish_icelandic_unemployed_es.md b/docs/_posts/ahmedlone127/2024-09-27-bert_twitter_spanish_icelandic_unemployed_es.md new file mode 100644 index 00000000000000..e586682b7ef226 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_twitter_spanish_icelandic_unemployed_es.md @@ -0,0 +1,98 @@ +--- +layout: model +title: Castilian, Spanish bert_twitter_spanish_icelandic_unemployed BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_spanish_icelandic_unemployed +date: 2024-09-27 +tags: [bert, es, open_source, sequence_classification, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_icelandic_unemployed_es_5.5.0_3.0_1727415926966.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_5.5.0_3.0_1727415926966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## 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 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +References + +https://huggingface.co/manueltonneau/bert-twitter-es-is-unemployed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_twitterfin_padding90model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_twitterfin_padding90model_pipeline_en.md new file mode 100644 index 00000000000000..773e18cfcac86e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_twitterfin_padding90model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_twitterfin_padding90model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: bert_twitterfin_padding90model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitterfin_padding90model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding90model_pipeline_en_5.5.0_3.0_1727408980490.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitterfin_padding90model_pipeline_en_5.5.0_3.0_1727408980490.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_twitterfin_padding90model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_twitterfin_padding90model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitterfin_padding90model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Realgon/bert_twitterfin_padding90model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_yelp_test_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_yelp_test_en.md new file mode 100644 index 00000000000000..29b551c6a6bf42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_yelp_test_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_yelp_test BertForSequenceClassification from wesleyaag +author: John Snow Labs +name: bert_yelp_test +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_yelp_test` is a English model originally trained by wesleyaag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_yelp_test_en_5.5.0_3.0_1727417193233.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_yelp_test_en_5.5.0_3.0_1727417193233.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_yelp_test","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_yelp_test", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_yelp_test| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/wesleyaag/bert-yelp-test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bert_yelp_test_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-bert_yelp_test_pipeline_en.md new file mode 100644 index 00000000000000..aba6f2b0728c1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bert_yelp_test_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_yelp_test_pipeline pipeline BertForSequenceClassification from wesleyaag +author: John Snow Labs +name: bert_yelp_test_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_yelp_test_pipeline` is a English model originally trained by wesleyaag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_yelp_test_pipeline_en_5.5.0_3.0_1727417218027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_yelp_test_pipeline_en_5.5.0_3.0_1727417218027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_yelp_test_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_yelp_test_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_yelp_test_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/wesleyaag/bert-yelp-test + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bertanswerabilityevaluator_en.md b/docs/_posts/ahmedlone127/2024-09-27-bertanswerabilityevaluator_en.md new file mode 100644 index 00000000000000..9cac26ae473c2d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bertanswerabilityevaluator_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bertanswerabilityevaluator BertForSequenceClassification from Bavanda +author: John Snow Labs +name: bertanswerabilityevaluator +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertanswerabilityevaluator` is a English model originally trained by Bavanda. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertanswerabilityevaluator_en_5.5.0_3.0_1727407362082.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertanswerabilityevaluator_en_5.5.0_3.0_1727407362082.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("bertanswerabilityevaluator","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertanswerabilityevaluator", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertanswerabilityevaluator| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Bavanda/BERTAnswerabilityEvaluator \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bertfordetectingdepression_twitter2015_en.md b/docs/_posts/ahmedlone127/2024-09-27-bertfordetectingdepression_twitter2015_en.md new file mode 100644 index 00000000000000..ac0e9c74d74e8d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bertfordetectingdepression_twitter2015_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bertfordetectingdepression_twitter2015 BertForSequenceClassification from Silicon23 +author: John Snow Labs +name: bertfordetectingdepression_twitter2015 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertfordetectingdepression_twitter2015` is a English model originally trained by Silicon23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertfordetectingdepression_twitter2015_en_5.5.0_3.0_1727412676193.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertfordetectingdepression_twitter2015_en_5.5.0_3.0_1727412676193.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("bertfordetectingdepression_twitter2015","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertfordetectingdepression_twitter2015", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertfordetectingdepression_twitter2015| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Silicon23/BERTForDetectingDepression-Twitter2015 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline_pt.md b/docs/_posts/ahmedlone127/2024-09-27-bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline_pt.md new file mode 100644 index 00000000000000..22c6925bf18356 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline_pt.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Portuguese bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline pipeline BertForSequenceClassification from Luciano +author: John Snow Labs +name: bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline +date: 2024-09-27 +tags: [pt, open_source, pipeline, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline` is a Portuguese model originally trained by Luciano. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline_pt_5.5.0_3.0_1727410739058.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline_pt_5.5.0_3.0_1727410739058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline", lang = "pt") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline", lang = "pt") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|pt| +|Size:|408.2 MB| + +## References + +https://huggingface.co/Luciano/bertimbau-base-finetuned-brazilian_court_decisions_bt8_ep15 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pt.md b/docs/_posts/ahmedlone127/2024-09-27-bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pt.md new file mode 100644 index 00000000000000..31a967afaf8cdf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pt.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Portuguese bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15 BertForSequenceClassification from Luciano +author: John Snow Labs +name: bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15 +date: 2024-09-27 +tags: [pt, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: pt +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_base_finetuned_brazilian_court_decisions_bt8_ep15` is a Portuguese model originally trained by Luciano. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pt_5.5.0_3.0_1727410718140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15_pt_5.5.0_3.0_1727410718140.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("bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15","pt") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15", "pt") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertimbau_base_finetuned_brazilian_court_decisions_bt8_ep15| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.2 MB| + +## References + +https://huggingface.co/Luciano/bertimbau-base-finetuned-brazilian_court_decisions_bt8_ep15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_16_42_en.md b/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_16_42_en.md new file mode 100644 index 00000000000000..fd14ce6abfe55e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_16_42_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English best_model_sst_2_16_42 BertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_sst_2_16_42 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_sst_2_16_42` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_sst_2_16_42_en_5.5.0_3.0_1727400549575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_sst_2_16_42_en_5.5.0_3.0_1727400549575.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("best_model_sst_2_16_42","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("best_model_sst_2_16_42", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_sst_2_16_42| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/best_model-sst-2-16-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_100_pipeline_en.md new file mode 100644 index 00000000000000..41919cce7fa639 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_100_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English best_model_sst_2_64_100_pipeline pipeline BertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_sst_2_64_100_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_sst_2_64_100_pipeline` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_sst_2_64_100_pipeline_en_5.5.0_3.0_1727403262672.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_sst_2_64_100_pipeline_en_5.5.0_3.0_1727403262672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("best_model_sst_2_64_100_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("best_model_sst_2_64_100_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_sst_2_64_100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/best_model-sst-2-64-100 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_42_en.md b/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_42_en.md new file mode 100644 index 00000000000000..de39b9e3e92fc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_42_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English best_model_sst_2_64_42 BertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_sst_2_64_42 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_sst_2_64_42` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_sst_2_64_42_en_5.5.0_3.0_1727411880634.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_sst_2_64_42_en_5.5.0_3.0_1727411880634.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("best_model_sst_2_64_42","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("best_model_sst_2_64_42", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_sst_2_64_42| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/best_model-sst-2-64-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_42_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_42_pipeline_en.md new file mode 100644 index 00000000000000..a4b01980453bdb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-best_model_sst_2_64_42_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English best_model_sst_2_64_42_pipeline pipeline BertForSequenceClassification from simonycl +author: John Snow Labs +name: best_model_sst_2_64_42_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_sst_2_64_42_pipeline` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_sst_2_64_42_pipeline_en_5.5.0_3.0_1727411902690.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_sst_2_64_42_pipeline_en_5.5.0_3.0_1727411902690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("best_model_sst_2_64_42_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("best_model_sst_2_64_42_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_sst_2_64_42_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/best_model-sst-2-64-42 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-best_model_with_bitfit_en.md b/docs/_posts/ahmedlone127/2024-09-27-best_model_with_bitfit_en.md new file mode 100644 index 00000000000000..d9363aa55e899c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-best_model_with_bitfit_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English best_model_with_bitfit BertForSequenceClassification from Mariaaaaa +author: John Snow Labs +name: best_model_with_bitfit +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`best_model_with_bitfit` is a English model originally trained by Mariaaaaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/best_model_with_bitfit_en_5.5.0_3.0_1727415573351.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/best_model_with_bitfit_en_5.5.0_3.0_1727415573351.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("best_model_with_bitfit","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("best_model_with_bitfit", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|best_model_with_bitfit| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Mariaaaaa/best_model_with_bitfit \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-biobert_base_cased_v11_finetuned_medicalcondition_en.md b/docs/_posts/ahmedlone127/2024-09-27-biobert_base_cased_v11_finetuned_medicalcondition_en.md new file mode 100644 index 00000000000000..4470643dcd7205 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-biobert_base_cased_v11_finetuned_medicalcondition_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English biobert_base_cased_v11_finetuned_medicalcondition BertForSequenceClassification from sid321axn +author: John Snow Labs +name: biobert_base_cased_v11_finetuned_medicalcondition +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_v11_finetuned_medicalcondition` is a English model originally trained by sid321axn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_base_cased_v11_finetuned_medicalcondition_en_5.5.0_3.0_1727405075604.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_base_cased_v11_finetuned_medicalcondition_en_5.5.0_3.0_1727405075604.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("biobert_base_cased_v11_finetuned_medicalcondition","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("biobert_base_cased_v11_finetuned_medicalcondition", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobert_base_cased_v11_finetuned_medicalcondition| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.4 MB| + +## References + +https://huggingface.co/sid321axn/biobert-base-cased-v11-finetuned-medicalcondition \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-book_review_sentiment_classification_ar.md b/docs/_posts/ahmedlone127/2024-09-27-book_review_sentiment_classification_ar.md new file mode 100644 index 00000000000000..42559812240ffb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-book_review_sentiment_classification_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic book_review_sentiment_classification BertForSequenceClassification from AbdallahNasir +author: John Snow Labs +name: book_review_sentiment_classification +date: 2024-09-27 +tags: [ar, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`book_review_sentiment_classification` is a Arabic model originally trained by AbdallahNasir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/book_review_sentiment_classification_ar_5.5.0_3.0_1727408484652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/book_review_sentiment_classification_ar_5.5.0_3.0_1727408484652.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("book_review_sentiment_classification","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("book_review_sentiment_classification", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|book_review_sentiment_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|608.8 MB| + +## References + +https://huggingface.co/AbdallahNasir/book-review-sentiment-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-book_review_sentiment_classification_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-09-27-book_review_sentiment_classification_pipeline_ar.md new file mode 100644 index 00000000000000..bb28f20a444487 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-book_review_sentiment_classification_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic book_review_sentiment_classification_pipeline pipeline BertForSequenceClassification from AbdallahNasir +author: John Snow Labs +name: book_review_sentiment_classification_pipeline +date: 2024-09-27 +tags: [ar, open_source, pipeline, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`book_review_sentiment_classification_pipeline` is a Arabic model originally trained by AbdallahNasir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/book_review_sentiment_classification_pipeline_ar_5.5.0_3.0_1727408519469.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/book_review_sentiment_classification_pipeline_ar_5.5.0_3.0_1727408519469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("book_review_sentiment_classification_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("book_review_sentiment_classification_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|book_review_sentiment_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|608.8 MB| + +## References + +https://huggingface.co/AbdallahNasir/book-review-sentiment-classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-boss_sentiment_12000_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-27-boss_sentiment_12000_bert_base_uncased_en.md new file mode 100644 index 00000000000000..ff0dbb7aefb338 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-boss_sentiment_12000_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English boss_sentiment_12000_bert_base_uncased BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: boss_sentiment_12000_bert_base_uncased +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_12000_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_12000_bert_base_uncased_en_5.5.0_3.0_1727406290671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boss_sentiment_12000_bert_base_uncased_en_5.5.0_3.0_1727406290671.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("boss_sentiment_12000_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("boss_sentiment_12000_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|boss_sentiment_12000_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/boss-sentiment-12000-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-boss_sentiment_24000_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-27-boss_sentiment_24000_bert_base_uncased_en.md new file mode 100644 index 00000000000000..808c29475aed50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-boss_sentiment_24000_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English boss_sentiment_24000_bert_base_uncased BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: boss_sentiment_24000_bert_base_uncased +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_24000_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_24000_bert_base_uncased_en_5.5.0_3.0_1727402638408.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boss_sentiment_24000_bert_base_uncased_en_5.5.0_3.0_1727402638408.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("boss_sentiment_24000_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("boss_sentiment_24000_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|boss_sentiment_24000_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/boss-sentiment-24000-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-burmese_bert_model_en.md b/docs/_posts/ahmedlone127/2024-09-27-burmese_bert_model_en.md new file mode 100644 index 00000000000000..ac00fd2a11d065 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-burmese_bert_model_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English burmese_bert_model BertEmbeddings from billfass +author: John Snow Labs +name: burmese_bert_model +date: 2024-09-27 +tags: [bert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_bert_model` is a English model originally trained by billfass. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_bert_model_en_5.5.0_3.0_1727414230950.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_bert_model_en_5.5.0_3.0_1727414230950.zip){:.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 =BertEmbeddings.pretrained("burmese_bert_model","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 = BertEmbeddings + .pretrained("burmese_bert_model", "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:|burmese_bert_model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +References + +https://huggingface.co/billfass/my_bert_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-burmese_bert_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-burmese_bert_model_pipeline_en.md new file mode 100644 index 00000000000000..d6e5758949ad79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-burmese_bert_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English burmese_bert_model_pipeline pipeline BertForSequenceClassification from abhikasar2015 +author: John Snow Labs +name: burmese_bert_model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_bert_model_pipeline` is a English model originally trained by abhikasar2015. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_bert_model_pipeline_en_5.5.0_3.0_1727414251830.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_bert_model_pipeline_en_5.5.0_3.0_1727414251830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_bert_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_bert_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_bert_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/abhikasar2015/my_bert_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cardinal_query_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-27-cardinal_query_classifier_en.md new file mode 100644 index 00000000000000..c66a53089d493b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cardinal_query_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cardinal_query_classifier BertForSequenceClassification from rehmatsg +author: John Snow Labs +name: cardinal_query_classifier +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cardinal_query_classifier` is a English model originally trained by rehmatsg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cardinal_query_classifier_en_5.5.0_3.0_1727410907276.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cardinal_query_classifier_en_5.5.0_3.0_1727410907276.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("cardinal_query_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cardinal_query_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cardinal_query_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rehmatsg/cardinal-query-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cardinal_query_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-cardinal_query_classifier_pipeline_en.md new file mode 100644 index 00000000000000..9b31d19e0169ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cardinal_query_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cardinal_query_classifier_pipeline pipeline BertForSequenceClassification from rehmatsg +author: John Snow Labs +name: cardinal_query_classifier_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cardinal_query_classifier_pipeline` is a English model originally trained by rehmatsg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cardinal_query_classifier_pipeline_en_5.5.0_3.0_1727410928355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cardinal_query_classifier_pipeline_en_5.5.0_3.0_1727410928355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cardinal_query_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cardinal_query_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cardinal_query_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/rehmatsg/cardinal-query-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-carlos_bert_v2_2_en.md b/docs/_posts/ahmedlone127/2024-09-27-carlos_bert_v2_2_en.md new file mode 100644 index 00000000000000..103a9fe2a61c7b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-carlos_bert_v2_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English carlos_bert_v2_2 BertForSequenceClassification from raasikhk +author: John Snow Labs +name: carlos_bert_v2_2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`carlos_bert_v2_2` is a English model originally trained by raasikhk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/carlos_bert_v2_2_en_5.5.0_3.0_1727410910984.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/carlos_bert_v2_2_en_5.5.0_3.0_1727410910984.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("carlos_bert_v2_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("carlos_bert_v2_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|carlos_bert_v2_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/raasikhk/carlos_bert_v2_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v3_en.md b/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v3_en.md new file mode 100644 index 00000000000000..ac9b8bbdc35dda --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English chinese_roberta_climate_transition_physical_risk_prediction_v3 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: chinese_roberta_climate_transition_physical_risk_prediction_v3 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_climate_transition_physical_risk_prediction_v3` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_transition_physical_risk_prediction_v3_en_5.5.0_3.0_1727417598970.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_transition_physical_risk_prediction_v3_en_5.5.0_3.0_1727417598970.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("chinese_roberta_climate_transition_physical_risk_prediction_v3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("chinese_roberta_climate_transition_physical_risk_prediction_v3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_climate_transition_physical_risk_prediction_v3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.2 MB| + +## References + +https://huggingface.co/hw2942/chinese-roberta-climate-transition-physical-risk-prediction-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline_en.md new file mode 100644 index 00000000000000..dd5a0d62095030 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline_en_5.5.0_3.0_1727417619177.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline_en_5.5.0_3.0_1727417619177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_climate_transition_physical_risk_prediction_v3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.2 MB| + +## References + +https://huggingface.co/hw2942/chinese-roberta-climate-transition-physical-risk-prediction-v3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v5_en.md b/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v5_en.md new file mode 100644 index 00000000000000..c6725c86ba08ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English chinese_roberta_climate_transition_physical_risk_prediction_v5 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: chinese_roberta_climate_transition_physical_risk_prediction_v5 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_climate_transition_physical_risk_prediction_v5` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_transition_physical_risk_prediction_v5_en_5.5.0_3.0_1727402556655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_transition_physical_risk_prediction_v5_en_5.5.0_3.0_1727402556655.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("chinese_roberta_climate_transition_physical_risk_prediction_v5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("chinese_roberta_climate_transition_physical_risk_prediction_v5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_climate_transition_physical_risk_prediction_v5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.2 MB| + +## References + +https://huggingface.co/hw2942/chinese-roberta-climate-transition-physical-risk-prediction-v5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline_en.md new file mode 100644 index 00000000000000..d69b0da97aa7b9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline_en_5.5.0_3.0_1727402576252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline_en_5.5.0_3.0_1727402576252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_climate_transition_physical_risk_prediction_v5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.2 MB| + +## References + +https://huggingface.co/hw2942/chinese-roberta-climate-transition-physical-risk-prediction-v5 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr0_seed0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr0_seed0_pipeline_en.md new file mode 100644 index 00000000000000..9b03166ac12e80 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr0_seed0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr0_seed0_pipeline pipeline BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr0_seed0_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr0_seed0_pipeline` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr0_seed0_pipeline_en_5.5.0_3.0_1727408547869.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr0_seed0_pipeline_en_5.5.0_3.0_1727408547869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cold_fusion_bert_base_uncased_itr0_seed0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cold_fusion_bert_base_uncased_itr0_seed0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr0_seed0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr0-seed0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr18_seed0_en.md b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr18_seed0_en.md new file mode 100644 index 00000000000000..dd707232890d4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr18_seed0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr18_seed0 BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr18_seed0 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr18_seed0` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr18_seed0_en_5.5.0_3.0_1727417791186.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr18_seed0_en_5.5.0_3.0_1727417791186.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("cold_fusion_bert_base_uncased_itr18_seed0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cold_fusion_bert_base_uncased_itr18_seed0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr18_seed0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr18-seed0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr18_seed0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr18_seed0_pipeline_en.md new file mode 100644 index 00000000000000..8cdbeb6a57c8f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr18_seed0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr18_seed0_pipeline pipeline BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr18_seed0_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr18_seed0_pipeline` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr18_seed0_pipeline_en_5.5.0_3.0_1727417816876.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr18_seed0_pipeline_en_5.5.0_3.0_1727417816876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cold_fusion_bert_base_uncased_itr18_seed0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cold_fusion_bert_base_uncased_itr18_seed0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr18_seed0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr18-seed0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr1_seed0_en.md b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr1_seed0_en.md new file mode 100644 index 00000000000000..600d54353a8d5a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr1_seed0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr1_seed0 BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr1_seed0 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr1_seed0` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr1_seed0_en_5.5.0_3.0_1727418686112.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr1_seed0_en_5.5.0_3.0_1727418686112.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("cold_fusion_bert_base_uncased_itr1_seed0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cold_fusion_bert_base_uncased_itr1_seed0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr1_seed0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr1-seed0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl_en.md b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl_en.md new file mode 100644 index 00000000000000..aecea113d6afd5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl BertForSequenceClassification from jakub014 +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl_en_5.5.0_3.0_1727418566802.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl_en_5.5.0_3.0_1727418566802.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("cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr23_seed0_finetuned_sufficiency_dagstuhl| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/ColD-Fusion-bert-base-uncased-itr23-seed0-finetuned-sufficiency-dagstuhl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr2_seed0_en.md b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr2_seed0_en.md new file mode 100644 index 00000000000000..a0065eb1ee71bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr2_seed0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr2_seed0 BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr2_seed0 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr2_seed0` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr2_seed0_en_5.5.0_3.0_1727417938814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr2_seed0_en_5.5.0_3.0_1727417938814.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("cold_fusion_bert_base_uncased_itr2_seed0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cold_fusion_bert_base_uncased_itr2_seed0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr2_seed0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr2-seed0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr2_seed0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr2_seed0_pipeline_en.md new file mode 100644 index 00000000000000..9b771868f7753a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cold_fusion_bert_base_uncased_itr2_seed0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English cold_fusion_bert_base_uncased_itr2_seed0_pipeline pipeline BertForSequenceClassification from ibm +author: John Snow Labs +name: cold_fusion_bert_base_uncased_itr2_seed0_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cold_fusion_bert_base_uncased_itr2_seed0_pipeline` is a English model originally trained by ibm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr2_seed0_pipeline_en_5.5.0_3.0_1727417959932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cold_fusion_bert_base_uncased_itr2_seed0_pipeline_en_5.5.0_3.0_1727417959932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cold_fusion_bert_base_uncased_itr2_seed0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cold_fusion_bert_base_uncased_itr2_seed0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cold_fusion_bert_base_uncased_itr2_seed0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/ibm/ColD-Fusion-bert-base-uncased-itr2-seed0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-comment_bert_subject_en.md b/docs/_posts/ahmedlone127/2024-09-27-comment_bert_subject_en.md new file mode 100644 index 00000000000000..0754701a26b952 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-comment_bert_subject_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English comment_bert_subject BertForSequenceClassification from mochodek +author: John Snow Labs +name: comment_bert_subject +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comment_bert_subject` is a English model originally trained by mochodek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comment_bert_subject_en_5.5.0_3.0_1727418742480.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comment_bert_subject_en_5.5.0_3.0_1727418742480.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("comment_bert_subject","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("comment_bert_subject", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|comment_bert_subject| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mochodek/comment-bert-subject \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-comment_bert_subject_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-comment_bert_subject_pipeline_en.md new file mode 100644 index 00000000000000..67704a16a89a92 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-comment_bert_subject_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English comment_bert_subject_pipeline pipeline BertForSequenceClassification from mochodek +author: John Snow Labs +name: comment_bert_subject_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`comment_bert_subject_pipeline` is a English model originally trained by mochodek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/comment_bert_subject_pipeline_en_5.5.0_3.0_1727418763615.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/comment_bert_subject_pipeline_en_5.5.0_3.0_1727418763615.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("comment_bert_subject_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("comment_bert_subject_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|comment_bert_subject_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mochodek/comment-bert-subject + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cs505_dev_csi_bert_base_multilingual_uncased_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-cs505_dev_csi_bert_base_multilingual_uncased_pipeline_xx.md new file mode 100644 index 00000000000000..67f9f2bca6f3ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cs505_dev_csi_bert_base_multilingual_uncased_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual cs505_dev_csi_bert_base_multilingual_uncased_pipeline pipeline BertForSequenceClassification from ThuyNT03 +author: John Snow Labs +name: cs505_dev_csi_bert_base_multilingual_uncased_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs505_dev_csi_bert_base_multilingual_uncased_pipeline` is a Multilingual model originally trained by ThuyNT03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs505_dev_csi_bert_base_multilingual_uncased_pipeline_xx_5.5.0_3.0_1727414058052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs505_dev_csi_bert_base_multilingual_uncased_pipeline_xx_5.5.0_3.0_1727414058052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cs505_dev_csi_bert_base_multilingual_uncased_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cs505_dev_csi_bert_base_multilingual_uncased_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cs505_dev_csi_bert_base_multilingual_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/ThuyNT03/CS505-Dev-CSI-bert-base-multilingual-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-cs505_dev_csi_bert_base_multilingual_uncased_xx.md b/docs/_posts/ahmedlone127/2024-09-27-cs505_dev_csi_bert_base_multilingual_uncased_xx.md new file mode 100644 index 00000000000000..4be64ca2aa9032 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-cs505_dev_csi_bert_base_multilingual_uncased_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual cs505_dev_csi_bert_base_multilingual_uncased BertForSequenceClassification from ThuyNT03 +author: John Snow Labs +name: cs505_dev_csi_bert_base_multilingual_uncased +date: 2024-09-27 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cs505_dev_csi_bert_base_multilingual_uncased` is a Multilingual model originally trained by ThuyNT03. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cs505_dev_csi_bert_base_multilingual_uncased_xx_5.5.0_3.0_1727414026330.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cs505_dev_csi_bert_base_multilingual_uncased_xx_5.5.0_3.0_1727414026330.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("cs505_dev_csi_bert_base_multilingual_uncased","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cs505_dev_csi_bert_base_multilingual_uncased", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cs505_dev_csi_bert_base_multilingual_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/ThuyNT03/CS505-Dev-CSI-bert-base-multilingual-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-curated_gender_equality_weighted_en.md b/docs/_posts/ahmedlone127/2024-09-27-curated_gender_equality_weighted_en.md new file mode 100644 index 00000000000000..dd1eda36644153 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-curated_gender_equality_weighted_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English curated_gender_equality_weighted BertForSequenceClassification from alex-miller +author: John Snow Labs +name: curated_gender_equality_weighted +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`curated_gender_equality_weighted` is a English model originally trained by alex-miller. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/curated_gender_equality_weighted_en_5.5.0_3.0_1727415485910.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/curated_gender_equality_weighted_en_5.5.0_3.0_1727415485910.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("curated_gender_equality_weighted","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("curated_gender_equality_weighted", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|curated_gender_equality_weighted| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|630.9 MB| + +## References + +https://huggingface.co/alex-miller/curated-gender-equality-weighted \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-customer_feedback_analysis_bert_en.md b/docs/_posts/ahmedlone127/2024-09-27-customer_feedback_analysis_bert_en.md new file mode 100644 index 00000000000000..fb08b65981f5df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-customer_feedback_analysis_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English customer_feedback_analysis_bert BertForSequenceClassification from interneuronai +author: John Snow Labs +name: customer_feedback_analysis_bert +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`customer_feedback_analysis_bert` is a English model originally trained by interneuronai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/customer_feedback_analysis_bert_en_5.5.0_3.0_1727404047265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/customer_feedback_analysis_bert_en_5.5.0_3.0_1727404047265.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("customer_feedback_analysis_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("customer_feedback_analysis_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|customer_feedback_analysis_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.8 MB| + +## References + +https://huggingface.co/interneuronai/customer_feedback_analysis_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-data103_bert_base_v1_en.md b/docs/_posts/ahmedlone127/2024-09-27-data103_bert_base_v1_en.md new file mode 100644 index 00000000000000..805e82d3068553 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-data103_bert_base_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English data103_bert_base_v1 BertForSequenceClassification from francheska-vicente +author: John Snow Labs +name: data103_bert_base_v1 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`data103_bert_base_v1` is a English model originally trained by francheska-vicente. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/data103_bert_base_v1_en_5.5.0_3.0_1727417545610.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/data103_bert_base_v1_en_5.5.0_3.0_1727417545610.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("data103_bert_base_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("data103_bert_base_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|data103_bert_base_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/francheska-vicente/data103-bert-base-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-dbpedia_classes_bert_base_uncased_few_100_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-dbpedia_classes_bert_base_uncased_few_100_pipeline_en.md new file mode 100644 index 00000000000000..7013a2dd5fdd68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-dbpedia_classes_bert_base_uncased_few_100_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dbpedia_classes_bert_base_uncased_few_100_pipeline pipeline BertForSequenceClassification from TheChickenAgent +author: John Snow Labs +name: dbpedia_classes_bert_base_uncased_few_100_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dbpedia_classes_bert_base_uncased_few_100_pipeline` is a English model originally trained by TheChickenAgent. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dbpedia_classes_bert_base_uncased_few_100_pipeline_en_5.5.0_3.0_1727416631945.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dbpedia_classes_bert_base_uncased_few_100_pipeline_en_5.5.0_3.0_1727416631945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dbpedia_classes_bert_base_uncased_few_100_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dbpedia_classes_bert_base_uncased_few_100_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dbpedia_classes_bert_base_uncased_few_100_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TheChickenAgent/DBPedia_Classes_BERT-base-uncased-few-100 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline_en.md new file mode 100644 index 00000000000000..54ba4fe86759b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline pipeline BertForSequenceClassification from halilibr +author: John Snow Labs +name: dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline` is a English model originally trained by halilibr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline_en_5.5.0_3.0_1727412666757.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline_en_5.5.0_3.0_1727412666757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dilbazlar_anxiety_disorder_binary_detection_model_acc_98_7_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|691.6 MB| + +## References + +https://huggingface.co/halilibr/dilbazlar-anxiety-disorder-binary-detection-model-acc-98.7 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_depression_disorders_recognition_turkish_model_acc_82_en.md b/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_depression_disorders_recognition_turkish_model_acc_82_en.md new file mode 100644 index 00000000000000..c7c6571254878d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_depression_disorders_recognition_turkish_model_acc_82_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dilbazlar_depression_disorders_recognition_turkish_model_acc_82 BertForSequenceClassification from halilibr +author: John Snow Labs +name: dilbazlar_depression_disorders_recognition_turkish_model_acc_82 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dilbazlar_depression_disorders_recognition_turkish_model_acc_82` is a English model originally trained by halilibr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dilbazlar_depression_disorders_recognition_turkish_model_acc_82_en_5.5.0_3.0_1727409995484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dilbazlar_depression_disorders_recognition_turkish_model_acc_82_en_5.5.0_3.0_1727409995484.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("dilbazlar_depression_disorders_recognition_turkish_model_acc_82","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dilbazlar_depression_disorders_recognition_turkish_model_acc_82", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dilbazlar_depression_disorders_recognition_turkish_model_acc_82| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|691.6 MB| + +## References + +https://huggingface.co/halilibr/dilbazlar-depression-disorders-recognition-tr-model-acc-82 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline_en.md new file mode 100644 index 00000000000000..cc4d86ca50afa3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline pipeline BertForSequenceClassification from halilibr +author: John Snow Labs +name: dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline` is a English model originally trained by halilibr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline_en_5.5.0_3.0_1727410029950.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline_en_5.5.0_3.0_1727410029950.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dilbazlar_depression_disorders_recognition_turkish_model_acc_82_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|691.6 MB| + +## References + +https://huggingface.co/halilibr/dilbazlar-depression-disorders-recognition-tr-model-acc-82 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-distilbert_contacts_en.md b/docs/_posts/ahmedlone127/2024-09-27-distilbert_contacts_en.md new file mode 100644 index 00000000000000..6744f70399877e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-distilbert_contacts_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_contacts BertForSequenceClassification from zkv +author: John Snow Labs +name: distilbert_contacts +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_contacts` is a English model originally trained by zkv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_contacts_en_5.5.0_3.0_1727405359050.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_contacts_en_5.5.0_3.0_1727405359050.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("distilbert_contacts","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("distilbert_contacts", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_contacts| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|109.5 MB| + +## References + +https://huggingface.co/zkv/distilbert_contacts \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-distillbert_distilled_ag_news_2_en.md b/docs/_posts/ahmedlone127/2024-09-27-distillbert_distilled_ag_news_2_en.md new file mode 100644 index 00000000000000..7c267e0749106f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-distillbert_distilled_ag_news_2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distillbert_distilled_ag_news_2 BertForSequenceClassification from odunola +author: John Snow Labs +name: distillbert_distilled_ag_news_2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_distilled_ag_news_2` is a English model originally trained by odunola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_distilled_ag_news_2_en_5.5.0_3.0_1727406428393.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_distilled_ag_news_2_en_5.5.0_3.0_1727406428393.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("distillbert_distilled_ag_news_2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("distillbert_distilled_ag_news_2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distillbert_distilled_ag_news_2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|53.9 MB| + +## References + +https://huggingface.co/odunola/distillbert-distilled-ag-news-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-distillbert_distilled_ag_news_2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-distillbert_distilled_ag_news_2_pipeline_en.md new file mode 100644 index 00000000000000..83b4f27be40043 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-distillbert_distilled_ag_news_2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distillbert_distilled_ag_news_2_pipeline pipeline BertForSequenceClassification from odunola +author: John Snow Labs +name: distillbert_distilled_ag_news_2_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillbert_distilled_ag_news_2_pipeline` is a English model originally trained by odunola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillbert_distilled_ag_news_2_pipeline_en_5.5.0_3.0_1727406431675.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillbert_distilled_ag_news_2_pipeline_en_5.5.0_3.0_1727406431675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distillbert_distilled_ag_news_2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distillbert_distilled_ag_news_2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distillbert_distilled_ag_news_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|54.0 MB| + +## References + +https://huggingface.co/odunola/distillbert-distilled-ag-news-2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-dknews_norwegian_bokml_bert_ai_classifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-dknews_norwegian_bokml_bert_ai_classifier_pipeline_en.md new file mode 100644 index 00000000000000..823c96944ce6cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-dknews_norwegian_bokml_bert_ai_classifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dknews_norwegian_bokml_bert_ai_classifier_pipeline pipeline BertForSequenceClassification from MinaAlmasi +author: John Snow Labs +name: dknews_norwegian_bokml_bert_ai_classifier_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dknews_norwegian_bokml_bert_ai_classifier_pipeline` is a English model originally trained by MinaAlmasi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dknews_norwegian_bokml_bert_ai_classifier_pipeline_en_5.5.0_3.0_1727409621038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dknews_norwegian_bokml_bert_ai_classifier_pipeline_en_5.5.0_3.0_1727409621038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dknews_norwegian_bokml_bert_ai_classifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dknews_norwegian_bokml_bert_ai_classifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dknews_norwegian_bokml_bert_ai_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/MinaAlmasi/dknews-NB-BERT-AI-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline_en.md new file mode 100644 index 00000000000000..16bfffb49dd59b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline pipeline BertForSequenceClassification from SivaResearch +author: John Snow Labs +name: dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline` is a English model originally trained by SivaResearch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline_en_5.5.0_3.0_1727402678726.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline_en_5.5.0_3.0_1727402678726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dsm_509_assignment_sentiment_analysis_bert_siva_gowtham_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/SivaResearch/DSM_509_Assignment_Sentiment_analysis_BERT_SIVA_GOWTHAM + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-emotion_turkish19_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-emotion_turkish19_pipeline_en.md new file mode 100644 index 00000000000000..581e08e5782f04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-emotion_turkish19_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English emotion_turkish19_pipeline pipeline BertForSequenceClassification from asude55 +author: John Snow Labs +name: emotion_turkish19_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_turkish19_pipeline` is a English model originally trained by asude55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_turkish19_pipeline_en_5.5.0_3.0_1727412770302.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_turkish19_pipeline_en_5.5.0_3.0_1727412770302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("emotion_turkish19_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("emotion_turkish19_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emotion_turkish19_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.5 MB| + +## References + +https://huggingface.co/asude55/emotion-turkish19 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-environmental_claims_vinoth24_en.md b/docs/_posts/ahmedlone127/2024-09-27-environmental_claims_vinoth24_en.md new file mode 100644 index 00000000000000..359cdb68b566e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-environmental_claims_vinoth24_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English environmental_claims_vinoth24 BertForSequenceClassification from Vinoth24 +author: John Snow Labs +name: environmental_claims_vinoth24 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`environmental_claims_vinoth24` is a English model originally trained by Vinoth24. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/environmental_claims_vinoth24_en_5.5.0_3.0_1727404914253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/environmental_claims_vinoth24_en_5.5.0_3.0_1727404914253.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("environmental_claims_vinoth24","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("environmental_claims_vinoth24", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|environmental_claims_vinoth24| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Vinoth24/environmental_claims \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-ey_sentenceclassification_en.md b/docs/_posts/ahmedlone127/2024-09-27-ey_sentenceclassification_en.md new file mode 100644 index 00000000000000..683905ffa2f493 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-ey_sentenceclassification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ey_sentenceclassification BertForSequenceClassification from simonmun +author: John Snow Labs +name: ey_sentenceclassification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ey_sentenceclassification` is a English model originally trained by simonmun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ey_sentenceclassification_en_5.5.0_3.0_1727412014606.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ey_sentenceclassification_en_5.5.0_3.0_1727412014606.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("ey_sentenceclassification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ey_sentenceclassification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ey_sentenceclassification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|345.1 MB| + +## References + +https://huggingface.co/simonmun/Ey_SentenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline_en.md new file mode 100644 index 00000000000000..999175529fcabc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline pipeline BertForSequenceClassification from simonestradasch +author: John Snow Labs +name: fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline` is a English model originally trained by simonestradasch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline_en_5.5.0_3.0_1727416085802.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline_en_5.5.0_3.0_1727416085802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fake_news_bert_base_spanish_wwm_cased_simonestradasch_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/simonestradasch/fake-news-bert-base-spanish-wwm-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_emoji_en.md b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_emoji_en.md new file mode 100644 index 00000000000000..4170a2d1fc74b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_emoji_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English fakenews_bert_base_cased_emoji BertForSequenceClassification from Denyol +author: John Snow Labs +name: fakenews_bert_base_cased_emoji +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fakenews_bert_base_cased_emoji` is a English model originally trained by Denyol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_emoji_en_5.5.0_3.0_1727407517696.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_emoji_en_5.5.0_3.0_1727407517696.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("fakenews_bert_base_cased_emoji","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fakenews_bert_base_cased_emoji", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fakenews_bert_base_cased_emoji| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Denyol/FakeNews-bert-base-cased-emoji \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_emoji_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_emoji_pipeline_en.md new file mode 100644 index 00000000000000..ce4387f47e9157 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_emoji_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fakenews_bert_base_cased_emoji_pipeline pipeline BertForSequenceClassification from Denyol +author: John Snow Labs +name: fakenews_bert_base_cased_emoji_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fakenews_bert_base_cased_emoji_pipeline` is a English model originally trained by Denyol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_emoji_pipeline_en_5.5.0_3.0_1727407538778.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_emoji_pipeline_en_5.5.0_3.0_1727407538778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fakenews_bert_base_cased_emoji_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fakenews_bert_base_cased_emoji_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fakenews_bert_base_cased_emoji_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Denyol/FakeNews-bert-base-cased-emoji + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_html_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_html_pipeline_en.md new file mode 100644 index 00000000000000..cecc698080b7d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_html_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fakenews_bert_base_cased_html_pipeline pipeline BertForSequenceClassification from Denyol +author: John Snow Labs +name: fakenews_bert_base_cased_html_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fakenews_bert_base_cased_html_pipeline` is a English model originally trained by Denyol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_html_pipeline_en_5.5.0_3.0_1727409819551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_html_pipeline_en_5.5.0_3.0_1727409819551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fakenews_bert_base_cased_html_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fakenews_bert_base_cased_html_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fakenews_bert_base_cased_html_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Denyol/FakeNews-bert-base-cased-html + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_lowercase_en.md b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_lowercase_en.md new file mode 100644 index 00000000000000..626e23c97fabfb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_lowercase_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English fakenews_bert_base_cased_lowercase BertForSequenceClassification from Denyol +author: John Snow Labs +name: fakenews_bert_base_cased_lowercase +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fakenews_bert_base_cased_lowercase` is a English model originally trained by Denyol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_lowercase_en_5.5.0_3.0_1727409391351.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_lowercase_en_5.5.0_3.0_1727409391351.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("fakenews_bert_base_cased_lowercase","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fakenews_bert_base_cased_lowercase", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fakenews_bert_base_cased_lowercase| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Denyol/FakeNews-bert-base-cased-lowercase \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_lowercase_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_lowercase_pipeline_en.md new file mode 100644 index 00000000000000..9367bb242b011a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_lowercase_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fakenews_bert_base_cased_lowercase_pipeline pipeline BertForSequenceClassification from Denyol +author: John Snow Labs +name: fakenews_bert_base_cased_lowercase_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fakenews_bert_base_cased_lowercase_pipeline` is a English model originally trained by Denyol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_lowercase_pipeline_en_5.5.0_3.0_1727409411898.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_lowercase_pipeline_en_5.5.0_3.0_1727409411898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fakenews_bert_base_cased_lowercase_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fakenews_bert_base_cased_lowercase_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fakenews_bert_base_cased_lowercase_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Denyol/FakeNews-bert-base-cased-lowercase + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_stopwords_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_stopwords_pipeline_en.md new file mode 100644 index 00000000000000..de406105503584 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fakenews_bert_base_cased_stopwords_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fakenews_bert_base_cased_stopwords_pipeline pipeline BertForSequenceClassification from Denyol +author: John Snow Labs +name: fakenews_bert_base_cased_stopwords_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fakenews_bert_base_cased_stopwords_pipeline` is a English model originally trained by Denyol. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_stopwords_pipeline_en_5.5.0_3.0_1727412466126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fakenews_bert_base_cased_stopwords_pipeline_en_5.5.0_3.0_1727412466126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fakenews_bert_base_cased_stopwords_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fakenews_bert_base_cased_stopwords_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fakenews_bert_base_cased_stopwords_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Denyol/FakeNews-bert-base-cased-stopwords + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fine_tune_embedd_sih_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-fine_tune_embedd_sih_pipeline_en.md new file mode 100644 index 00000000000000..7a3a3ac6090fe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fine_tune_embedd_sih_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tune_embedd_sih_pipeline pipeline BertForSequenceClassification from shashaaa +author: John Snow Labs +name: fine_tune_embedd_sih_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_embedd_sih_pipeline` is a English model originally trained by shashaaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_embedd_sih_pipeline_en_5.5.0_3.0_1727404252819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_embedd_sih_pipeline_en_5.5.0_3.0_1727404252819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tune_embedd_sih_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tune_embedd_sih_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_embedd_sih_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|84.5 MB| + +## References + +https://huggingface.co/shashaaa/fine_tune_embedd_SIH + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_en.md b/docs/_posts/ahmedlone127/2024-09-27-fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_en.md new file mode 100644 index 00000000000000..80945463937d76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05 BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_lr_1e_05` 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_lr_1e_05_en_5.5.0_3.0_1727415293850.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_lr_1e_05_en_5.5.0_3.0_1727415293850.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("fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-IndoNLI-Augmented-with-indobert-base-uncased-LR-1e-05 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline_en.md new file mode 100644 index 00000000000000..587d781547a427 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline pipeline BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline` 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_lr_1e_05_pipeline_en_5.5.0_3.0_1727415315659.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_lr_1e_05_pipeline_en_5.5.0_3.0_1727415315659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_augmented_with_indobert_base_uncased_lr_1e_05_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.0 MB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-IndoNLI-Augmented-with-indobert-base-uncased-LR-1e-05 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-finetuned_bert_own_fixed_6_epoch_32_en.md b/docs/_posts/ahmedlone127/2024-09-27-finetuned_bert_own_fixed_6_epoch_32_en.md new file mode 100644 index 00000000000000..d62e91173b0088 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-finetuned_bert_own_fixed_6_epoch_32_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_bert_own_fixed_6_epoch_32 BertForSequenceClassification from UO282436 +author: John Snow Labs +name: finetuned_bert_own_fixed_6_epoch_32 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_own_fixed_6_epoch_32` is a English model originally trained by UO282436. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_own_fixed_6_epoch_32_en_5.5.0_3.0_1727400781010.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_own_fixed_6_epoch_32_en_5.5.0_3.0_1727400781010.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("finetuned_bert_own_fixed_6_epoch_32","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_bert_own_fixed_6_epoch_32", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_own_fixed_6_epoch_32| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/UO282436/finetuned-bert-own-fixed-6-epoch-32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-finetuned_sentiment_classfication_bert_model_slygags_en.md b/docs/_posts/ahmedlone127/2024-09-27-finetuned_sentiment_classfication_bert_model_slygags_en.md new file mode 100644 index 00000000000000..bb3fedc10fadb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-finetuned_sentiment_classfication_bert_model_slygags_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_sentiment_classfication_bert_model_slygags BertForSequenceClassification from Slygags +author: John Snow Labs +name: finetuned_sentiment_classfication_bert_model_slygags +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_sentiment_classfication_bert_model_slygags` is a English model originally trained by Slygags. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_classfication_bert_model_slygags_en_5.5.0_3.0_1727405215639.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_classfication_bert_model_slygags_en_5.5.0_3.0_1727405215639.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("finetuned_sentiment_classfication_bert_model_slygags","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_sentiment_classfication_bert_model_slygags", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sentiment_classfication_bert_model_slygags| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Slygags/finetuned-Sentiment-classfication-BERT-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-finetuned_sentiment_classfication_bert_model_slygags_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-finetuned_sentiment_classfication_bert_model_slygags_pipeline_en.md new file mode 100644 index 00000000000000..26a2d28bd714d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-finetuned_sentiment_classfication_bert_model_slygags_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_sentiment_classfication_bert_model_slygags_pipeline pipeline BertForSequenceClassification from Slygags +author: John Snow Labs +name: finetuned_sentiment_classfication_bert_model_slygags_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentiment_classfication_bert_model_slygags_pipeline` is a English model originally trained by Slygags. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_classfication_bert_model_slygags_pipeline_en_5.5.0_3.0_1727405236526.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentiment_classfication_bert_model_slygags_pipeline_en_5.5.0_3.0_1727405236526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_sentiment_classfication_bert_model_slygags_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_sentiment_classfication_bert_model_slygags_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sentiment_classfication_bert_model_slygags_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Slygags/finetuned-Sentiment-classfication-BERT-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_imdb_en.md b/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_imdb_en.md new file mode 100644 index 00000000000000..9fb2077517af71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_imdb_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_bert_base_uncased_on_imdb BertForSequenceClassification from Ibrahim-Alam +author: John Snow Labs +name: finetuning_bert_base_uncased_on_imdb +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_bert_base_uncased_on_imdb` is a English model originally trained by Ibrahim-Alam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_bert_base_uncased_on_imdb_en_5.5.0_3.0_1727415009153.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_bert_base_uncased_on_imdb_en_5.5.0_3.0_1727415009153.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("finetuning_bert_base_uncased_on_imdb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuning_bert_base_uncased_on_imdb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_bert_base_uncased_on_imdb| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ibrahim-Alam/finetuning-bert-base-uncased-on-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_imdb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_imdb_pipeline_en.md new file mode 100644 index 00000000000000..99c3071ee9a473 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_imdb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_bert_base_uncased_on_imdb_pipeline pipeline BertForSequenceClassification from Ibrahim-Alam +author: John Snow Labs +name: finetuning_bert_base_uncased_on_imdb_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_bert_base_uncased_on_imdb_pipeline` is a English model originally trained by Ibrahim-Alam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_bert_base_uncased_on_imdb_pipeline_en_5.5.0_3.0_1727415031155.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_bert_base_uncased_on_imdb_pipeline_en_5.5.0_3.0_1727415031155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_bert_base_uncased_on_imdb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_bert_base_uncased_on_imdb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_bert_base_uncased_on_imdb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ibrahim-Alam/finetuning-bert-base-uncased-on-imdb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_sst2_7000_samples_en.md b/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_sst2_7000_samples_en.md new file mode 100644 index 00000000000000..7bd1e3f339ea01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_sst2_7000_samples_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuning_bert_base_uncased_on_sst2_7000_samples BertForSequenceClassification from Ibrahim-Alam +author: John Snow Labs +name: finetuning_bert_base_uncased_on_sst2_7000_samples +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_bert_base_uncased_on_sst2_7000_samples` is a English model originally trained by Ibrahim-Alam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_bert_base_uncased_on_sst2_7000_samples_en_5.5.0_3.0_1727418519325.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_bert_base_uncased_on_sst2_7000_samples_en_5.5.0_3.0_1727418519325.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("finetuning_bert_base_uncased_on_sst2_7000_samples","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuning_bert_base_uncased_on_sst2_7000_samples", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_bert_base_uncased_on_sst2_7000_samples| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ibrahim-Alam/finetuning-bert-base-uncased-on-sst2_7000_samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline_en.md new file mode 100644 index 00000000000000..5f3776ee5fa488 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline pipeline BertForSequenceClassification from Ibrahim-Alam +author: John Snow Labs +name: finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline` is a English model originally trained by Ibrahim-Alam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline_en_5.5.0_3.0_1727418540926.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline_en_5.5.0_3.0_1727418540926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuning_bert_base_uncased_on_sst2_7000_samples_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ibrahim-Alam/finetuning-bert-base-uncased-on-sst2_7000_samples + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-first_dir_en.md b/docs/_posts/ahmedlone127/2024-09-27-first_dir_en.md new file mode 100644 index 00000000000000..a8cbb200409319 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-first_dir_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English first_dir BertForSequenceClassification from cfigueroa +author: John Snow Labs +name: first_dir +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`first_dir` is a English model originally trained by cfigueroa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/first_dir_en_5.5.0_3.0_1727407948435.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/first_dir_en_5.5.0_3.0_1727407948435.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("first_dir","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("first_dir", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|first_dir| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/cfigueroa/first_dir \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-first_dir_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-first_dir_pipeline_en.md new file mode 100644 index 00000000000000..8a499771d9979c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-first_dir_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English first_dir_pipeline pipeline BertForSequenceClassification from cfigueroa +author: John Snow Labs +name: first_dir_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`first_dir_pipeline` is a English model originally trained by cfigueroa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/first_dir_pipeline_en_5.5.0_3.0_1727407968928.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/first_dir_pipeline_en_5.5.0_3.0_1727407968928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("first_dir_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("first_dir_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|first_dir_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/cfigueroa/first_dir + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-frugalscore_small_bert_base_bert_score_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-frugalscore_small_bert_base_bert_score_pipeline_en.md new file mode 100644 index 00000000000000..91a2f1909249cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-frugalscore_small_bert_base_bert_score_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English frugalscore_small_bert_base_bert_score_pipeline pipeline BertForSequenceClassification from moussaKam +author: John Snow Labs +name: frugalscore_small_bert_base_bert_score_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`frugalscore_small_bert_base_bert_score_pipeline` is a English model originally trained by moussaKam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/frugalscore_small_bert_base_bert_score_pipeline_en_5.5.0_3.0_1727403526867.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/frugalscore_small_bert_base_bert_score_pipeline_en_5.5.0_3.0_1727403526867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("frugalscore_small_bert_base_bert_score_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("frugalscore_small_bert_base_bert_score_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|frugalscore_small_bert_base_bert_score_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|108.0 MB| + +## References + +https://huggingface.co/moussaKam/frugalscore_small_bert-base_bert-score + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-ft_bert_task3_en.md b/docs/_posts/ahmedlone127/2024-09-27-ft_bert_task3_en.md new file mode 100644 index 00000000000000..a5974a33c8989c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-ft_bert_task3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ft_bert_task3 BertForSequenceClassification from cungnlp +author: John Snow Labs +name: ft_bert_task3 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_bert_task3` is a English model originally trained by cungnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_bert_task3_en_5.5.0_3.0_1727395685745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_bert_task3_en_5.5.0_3.0_1727395685745.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("ft_bert_task3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ft_bert_task3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ft_bert_task3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/cungnlp/FT-BERT-Task3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-ft_bert_task3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-ft_bert_task3_pipeline_en.md new file mode 100644 index 00000000000000..8ad881d56f09a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-ft_bert_task3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ft_bert_task3_pipeline pipeline BertForSequenceClassification from cungnlp +author: John Snow Labs +name: ft_bert_task3_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ft_bert_task3_pipeline` is a English model originally trained by cungnlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ft_bert_task3_pipeline_en_5.5.0_3.0_1727395706549.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ft_bert_task3_pipeline_en_5.5.0_3.0_1727395706549.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ft_bert_task3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ft_bert_task3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ft_bert_task3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/cungnlp/FT-BERT-Task3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-german_medbert_de.md b/docs/_posts/ahmedlone127/2024-09-27-german_medbert_de.md new file mode 100644 index 00000000000000..2dce02a1ca521c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-german_medbert_de.md @@ -0,0 +1,92 @@ +--- +layout: model +title: German german_medbert BertEmbeddings from smanjil +author: John Snow Labs +name: german_medbert +date: 2024-09-27 +tags: [bert, de, open_source, fill_mask, onnx] +task: Embeddings +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_medbert` is a German model originally trained by smanjil. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_medbert_de_5.5.0_3.0_1727416934149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_medbert_de_5.5.0_3.0_1727416934149.zip){:.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 =BertEmbeddings.pretrained("german_medbert","de") \ + .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 = BertEmbeddings + .pretrained("german_medbert", "de") + .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:|german_medbert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|409.1 MB| + +## References + +References + +https://huggingface.co/smanjil/German-MedBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-goemotions_bertspanish_finetunig_f_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-goemotions_bertspanish_finetunig_f_pipeline_en.md new file mode 100644 index 00000000000000..7dec89b108d92f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-goemotions_bertspanish_finetunig_f_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English goemotions_bertspanish_finetunig_f_pipeline pipeline BertForSequenceClassification from mrovejaxd +author: John Snow Labs +name: goemotions_bertspanish_finetunig_f_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goemotions_bertspanish_finetunig_f_pipeline` is a English model originally trained by mrovejaxd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goemotions_bertspanish_finetunig_f_pipeline_en_5.5.0_3.0_1727409588801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goemotions_bertspanish_finetunig_f_pipeline_en_5.5.0_3.0_1727409588801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("goemotions_bertspanish_finetunig_f_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("goemotions_bertspanish_finetunig_f_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goemotions_bertspanish_finetunig_f_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.8 MB| + +## References + +https://huggingface.co/mrovejaxd/goemotions_bertspanish_finetunig_f + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-google_query_rating_en.md b/docs/_posts/ahmedlone127/2024-09-27-google_query_rating_en.md new file mode 100644 index 00000000000000..327590829fa0f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-google_query_rating_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English google_query_rating BertForSequenceClassification from Yanni8 +author: John Snow Labs +name: google_query_rating +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_query_rating` is a English model originally trained by Yanni8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_query_rating_en_5.5.0_3.0_1727409320161.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_query_rating_en_5.5.0_3.0_1727409320161.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("google_query_rating","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("google_query_rating", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|google_query_rating| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Yanni8/google-query-rating \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-google_query_rating_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-google_query_rating_pipeline_en.md new file mode 100644 index 00000000000000..1ca12c483733c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-google_query_rating_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English google_query_rating_pipeline pipeline BertForSequenceClassification from Yanni8 +author: John Snow Labs +name: google_query_rating_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_query_rating_pipeline` is a English model originally trained by Yanni8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_query_rating_pipeline_en_5.5.0_3.0_1727409341620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_query_rating_pipeline_en_5.5.0_3.0_1727409341620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("google_query_rating_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("google_query_rating_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|google_query_rating_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Yanni8/google-query-rating + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-gut_1024_finetuned_lora_bert_large_t2t_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-gut_1024_finetuned_lora_bert_large_t2t_pipeline_en.md new file mode 100644 index 00000000000000..8c280f905da69d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-gut_1024_finetuned_lora_bert_large_t2t_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English gut_1024_finetuned_lora_bert_large_t2t_pipeline pipeline BertForSequenceClassification from LiukG +author: John Snow Labs +name: gut_1024_finetuned_lora_bert_large_t2t_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gut_1024_finetuned_lora_bert_large_t2t_pipeline` is a English model originally trained by LiukG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gut_1024_finetuned_lora_bert_large_t2t_pipeline_en_5.5.0_3.0_1727416273465.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gut_1024_finetuned_lora_bert_large_t2t_pipeline_en_5.5.0_3.0_1727416273465.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("gut_1024_finetuned_lora_bert_large_t2t_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("gut_1024_finetuned_lora_bert_large_t2t_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gut_1024_finetuned_lora_bert_large_t2t_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/LiukG/gut_1024-finetuned-lora-bert-large-t2t + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hamorspammodel_en.md b/docs/_posts/ahmedlone127/2024-09-27-hamorspammodel_en.md new file mode 100644 index 00000000000000..bbf8a4bbb430d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hamorspammodel_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hamorspammodel BertForSequenceClassification from IreNkweke +author: John Snow Labs +name: hamorspammodel +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hamorspammodel` is a English model originally trained by IreNkweke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hamorspammodel_en_5.5.0_3.0_1727418437585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hamorspammodel_en_5.5.0_3.0_1727418437585.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("hamorspammodel","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hamorspammodel", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hamorspammodel| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/IreNkweke/HamOrSpamModel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hamorspammodel_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-hamorspammodel_pipeline_en.md new file mode 100644 index 00000000000000..9a7e8698873bdc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hamorspammodel_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hamorspammodel_pipeline pipeline BertForSequenceClassification from IreNkweke +author: John Snow Labs +name: hamorspammodel_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hamorspammodel_pipeline` is a English model originally trained by IreNkweke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hamorspammodel_pipeline_en_5.5.0_3.0_1727418464282.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hamorspammodel_pipeline_en_5.5.0_3.0_1727418464282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hamorspammodel_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hamorspammodel_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hamorspammodel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/IreNkweke/HamOrSpamModel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-09-27-hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline_xx.md new file mode 100644 index 00000000000000..25569467fb0aee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline pipeline BertForSequenceClassification from SiddharthaM +author: John Snow Labs +name: hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline +date: 2024-09-27 +tags: [xx, open_source, pipeline, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline` is a Multilingual model originally trained by SiddharthaM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline_xx_5.5.0_3.0_1727406805475.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline_xx_5.5.0_3.0_1727406805475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/SiddharthaM/hasoc19-bert-base-multilingual-cased-sentiment-new + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_xx.md b/docs/_posts/ahmedlone127/2024-09-27-hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_xx.md new file mode 100644 index 00000000000000..33f02c6a630e4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa BertForSequenceClassification from SiddharthaM +author: John Snow Labs +name: hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa +date: 2024-09-27 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa` is a Multilingual model originally trained by SiddharthaM. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_xx_5.5.0_3.0_1727406771556.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa_xx_5.5.0_3.0_1727406771556.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("hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hasoc19_bert_base_multilingual_cased_sentiment_nepal_bhasa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/SiddharthaM/hasoc19-bert-base-multilingual-cased-sentiment-new \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hatebert_edos_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-hatebert_edos_pipeline_en.md new file mode 100644 index 00000000000000..931fe03f405df0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hatebert_edos_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hatebert_edos_pipeline pipeline BertForSequenceClassification from clincolnoz +author: John Snow Labs +name: hatebert_edos_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hatebert_edos_pipeline` is a English model originally trained by clincolnoz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatebert_edos_pipeline_en_5.5.0_3.0_1727409950554.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatebert_edos_pipeline_en_5.5.0_3.0_1727409950554.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hatebert_edos_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hatebert_edos_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hatebert_edos_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.4 MB| + +## References + +https://huggingface.co/clincolnoz/HateBERT-edos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hatexplain_majority_relabeled_en.md b/docs/_posts/ahmedlone127/2024-09-27-hatexplain_majority_relabeled_en.md new file mode 100644 index 00000000000000..2cb98f2ce209cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hatexplain_majority_relabeled_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hatexplain_majority_relabeled BertForSequenceClassification from jkhan447 +author: John Snow Labs +name: hatexplain_majority_relabeled +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hatexplain_majority_relabeled` is a English model originally trained by jkhan447. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatexplain_majority_relabeled_en_5.5.0_3.0_1727402985934.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatexplain_majority_relabeled_en_5.5.0_3.0_1727402985934.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("hatexplain_majority_relabeled","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hatexplain_majority_relabeled", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hatexplain_majority_relabeled| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jkhan447/HateXplain-Majority-Relabeled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hatexplain_majority_relabeled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-hatexplain_majority_relabeled_pipeline_en.md new file mode 100644 index 00000000000000..d3f1661d01d7c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hatexplain_majority_relabeled_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hatexplain_majority_relabeled_pipeline pipeline BertForSequenceClassification from jkhan447 +author: John Snow Labs +name: hatexplain_majority_relabeled_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hatexplain_majority_relabeled_pipeline` is a English model originally trained by jkhan447. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatexplain_majority_relabeled_pipeline_en_5.5.0_3.0_1727403008820.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatexplain_majority_relabeled_pipeline_en_5.5.0_3.0_1727403008820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hatexplain_majority_relabeled_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hatexplain_majority_relabeled_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hatexplain_majority_relabeled_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jkhan447/HateXplain-Majority-Relabeled + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hatexplain_weighted_agreement_labeled_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-hatexplain_weighted_agreement_labeled_pipeline_en.md new file mode 100644 index 00000000000000..7e402b031c655f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hatexplain_weighted_agreement_labeled_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hatexplain_weighted_agreement_labeled_pipeline pipeline BertForSequenceClassification from jkhan447 +author: John Snow Labs +name: hatexplain_weighted_agreement_labeled_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hatexplain_weighted_agreement_labeled_pipeline` is a English model originally trained by jkhan447. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatexplain_weighted_agreement_labeled_pipeline_en_5.5.0_3.0_1727403376782.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatexplain_weighted_agreement_labeled_pipeline_en_5.5.0_3.0_1727403376782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hatexplain_weighted_agreement_labeled_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hatexplain_weighted_agreement_labeled_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hatexplain_weighted_agreement_labeled_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jkhan447/HateXplain-weighted-agreement-labeled + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-headline_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-headline_classification_en.md new file mode 100644 index 00000000000000..4cff86a4cb0ed9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-headline_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English headline_classification BertForSequenceClassification from freud-sensei +author: John Snow Labs +name: headline_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`headline_classification` is a English model originally trained by freud-sensei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/headline_classification_en_5.5.0_3.0_1727399774719.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/headline_classification_en_5.5.0_3.0_1727399774719.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("headline_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("headline_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|headline_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/freud-sensei/headline_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-headline_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-headline_classification_pipeline_en.md new file mode 100644 index 00000000000000..822d58cb395e2f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-headline_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English headline_classification_pipeline pipeline BertForSequenceClassification from freud-sensei +author: John Snow Labs +name: headline_classification_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`headline_classification_pipeline` is a English model originally trained by freud-sensei. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/headline_classification_pipeline_en_5.5.0_3.0_1727399796466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/headline_classification_pipeline_en_5.5.0_3.0_1727399796466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("headline_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("headline_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|headline_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/freud-sensei/headline_classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hw1_model_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-27-hw1_model_finetuned_en.md new file mode 100644 index 00000000000000..29dec855075328 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hw1_model_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hw1_model_finetuned BertForSequenceClassification from ganse +author: John Snow Labs +name: hw1_model_finetuned +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw1_model_finetuned` is a English model originally trained by ganse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_model_finetuned_en_5.5.0_3.0_1727411924500.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_model_finetuned_en_5.5.0_3.0_1727411924500.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("hw1_model_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hw1_model_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hw1_model_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ganse/HW1_model_finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hw1_model_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-hw1_model_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..78aff8c9664efe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hw1_model_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hw1_model_finetuned_pipeline pipeline BertForSequenceClassification from ganse +author: John Snow Labs +name: hw1_model_finetuned_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw1_model_finetuned_pipeline` is a English model originally trained by ganse. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_model_finetuned_pipeline_en_5.5.0_3.0_1727411945046.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_model_finetuned_pipeline_en_5.5.0_3.0_1727411945046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hw1_model_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hw1_model_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hw1_model_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ganse/HW1_model_finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hw2_demographic_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-hw2_demographic_model_pipeline_en.md new file mode 100644 index 00000000000000..143d708983a5d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hw2_demographic_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hw2_demographic_model_pipeline pipeline BertForSequenceClassification from rosavitiello +author: John Snow Labs +name: hw2_demographic_model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw2_demographic_model_pipeline` is a English model originally trained by rosavitiello. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw2_demographic_model_pipeline_en_5.5.0_3.0_1727398442711.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw2_demographic_model_pipeline_en_5.5.0_3.0_1727398442711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hw2_demographic_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hw2_demographic_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hw2_demographic_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.5 MB| + +## References + +https://huggingface.co/rosavitiello/hw2-demographic-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hyp_only_hum_filtered_en.md b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_hum_filtered_en.md new file mode 100644 index 00000000000000..70bb28c294b61b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_hum_filtered_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hyp_only_hum_filtered BertForSequenceClassification from grace-pro +author: John Snow Labs +name: hyp_only_hum_filtered +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hyp_only_hum_filtered` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hyp_only_hum_filtered_en_5.5.0_3.0_1727414362537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hyp_only_hum_filtered_en_5.5.0_3.0_1727414362537.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("hyp_only_hum_filtered","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hyp_only_hum_filtered", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hyp_only_hum_filtered| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/hyp_only_hum_filtered \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hyp_only_hum_filtered_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_hum_filtered_pipeline_en.md new file mode 100644 index 00000000000000..d3e48ac9d6b722 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_hum_filtered_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hyp_only_hum_filtered_pipeline pipeline BertForSequenceClassification from grace-pro +author: John Snow Labs +name: hyp_only_hum_filtered_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hyp_only_hum_filtered_pipeline` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hyp_only_hum_filtered_pipeline_en_5.5.0_3.0_1727414386137.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hyp_only_hum_filtered_pipeline_en_5.5.0_3.0_1727414386137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hyp_only_hum_filtered_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hyp_only_hum_filtered_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hyp_only_hum_filtered_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/hyp_only_hum_filtered + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hyp_only_machine_gen_temp_0_5_en.md b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_machine_gen_temp_0_5_en.md new file mode 100644 index 00000000000000..f627f26cebbdbf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_machine_gen_temp_0_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hyp_only_machine_gen_temp_0_5 BertForSequenceClassification from grace-pro +author: John Snow Labs +name: hyp_only_machine_gen_temp_0_5 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hyp_only_machine_gen_temp_0_5` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hyp_only_machine_gen_temp_0_5_en_5.5.0_3.0_1727419464684.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hyp_only_machine_gen_temp_0_5_en_5.5.0_3.0_1727419464684.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("hyp_only_machine_gen_temp_0_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hyp_only_machine_gen_temp_0_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hyp_only_machine_gen_temp_0_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/hyp_only_machine_gen_temp_0_5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hyp_only_snli_filtered_final_en.md b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_snli_filtered_final_en.md new file mode 100644 index 00000000000000..0ca69de342583e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_snli_filtered_final_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hyp_only_snli_filtered_final BertForSequenceClassification from grace-pro +author: John Snow Labs +name: hyp_only_snli_filtered_final +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hyp_only_snli_filtered_final` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hyp_only_snli_filtered_final_en_5.5.0_3.0_1727416144002.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hyp_only_snli_filtered_final_en_5.5.0_3.0_1727416144002.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("hyp_only_snli_filtered_final","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hyp_only_snli_filtered_final", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hyp_only_snli_filtered_final| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/hyp_only_snli_filtered_final \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-hyp_only_snli_filtered_final_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_snli_filtered_final_pipeline_en.md new file mode 100644 index 00000000000000..b3c2a7f714693c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-hyp_only_snli_filtered_final_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hyp_only_snli_filtered_final_pipeline pipeline BertForSequenceClassification from grace-pro +author: John Snow Labs +name: hyp_only_snli_filtered_final_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hyp_only_snli_filtered_final_pipeline` is a English model originally trained by grace-pro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hyp_only_snli_filtered_final_pipeline_en_5.5.0_3.0_1727416164851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hyp_only_snli_filtered_final_pipeline_en_5.5.0_3.0_1727416164851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hyp_only_snli_filtered_final_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hyp_only_snli_filtered_final_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hyp_only_snli_filtered_final_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grace-pro/hyp_only_snli_filtered_final + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-improved_arabert_twitter_sentiment_twitter_en.md b/docs/_posts/ahmedlone127/2024-09-27-improved_arabert_twitter_sentiment_twitter_en.md new file mode 100644 index 00000000000000..e9a8f984457b6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-improved_arabert_twitter_sentiment_twitter_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English improved_arabert_twitter_sentiment_twitter BertForSequenceClassification from Anwaarma +author: John Snow Labs +name: improved_arabert_twitter_sentiment_twitter +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`improved_arabert_twitter_sentiment_twitter` is a English model originally trained by Anwaarma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/improved_arabert_twitter_sentiment_twitter_en_5.5.0_3.0_1727399482873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/improved_arabert_twitter_sentiment_twitter_en_5.5.0_3.0_1727399482873.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("improved_arabert_twitter_sentiment_twitter","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("improved_arabert_twitter_sentiment_twitter", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|improved_arabert_twitter_sentiment_twitter| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/Anwaarma/Improved-Arabert-twitter-sentiment-Twitter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-indobert_base_p1_reddit_indonesia_sarcastic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-indobert_base_p1_reddit_indonesia_sarcastic_pipeline_en.md new file mode 100644 index 00000000000000..94e37191d2e559 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-indobert_base_p1_reddit_indonesia_sarcastic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English indobert_base_p1_reddit_indonesia_sarcastic_pipeline pipeline BertForSequenceClassification from w11wo +author: John Snow Labs +name: indobert_base_p1_reddit_indonesia_sarcastic_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_base_p1_reddit_indonesia_sarcastic_pipeline` is a English model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_base_p1_reddit_indonesia_sarcastic_pipeline_en_5.5.0_3.0_1727416326263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_base_p1_reddit_indonesia_sarcastic_pipeline_en_5.5.0_3.0_1727416326263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indobert_base_p1_reddit_indonesia_sarcastic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indobert_base_p1_reddit_indonesia_sarcastic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_base_p1_reddit_indonesia_sarcastic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.4 MB| + +## References + +https://huggingface.co/w11wo/indobert-base-p1-reddit-indonesia-sarcastic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-init_bert_ft_qqp_33_en.md b/docs/_posts/ahmedlone127/2024-09-27-init_bert_ft_qqp_33_en.md new file mode 100644 index 00000000000000..35498758a38a33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-init_bert_ft_qqp_33_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English init_bert_ft_qqp_33 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: init_bert_ft_qqp_33 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`init_bert_ft_qqp_33` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/init_bert_ft_qqp_33_en_5.5.0_3.0_1727418056257.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/init_bert_ft_qqp_33_en_5.5.0_3.0_1727418056257.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("init_bert_ft_qqp_33","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("init_bert_ft_qqp_33", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|init_bert_ft_qqp_33| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/init_bert_ft_qqp-33 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-init_bert_ft_qqp_33_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-init_bert_ft_qqp_33_pipeline_en.md new file mode 100644 index 00000000000000..85214ac08ebe07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-init_bert_ft_qqp_33_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English init_bert_ft_qqp_33_pipeline pipeline BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: init_bert_ft_qqp_33_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`init_bert_ft_qqp_33_pipeline` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/init_bert_ft_qqp_33_pipeline_en_5.5.0_3.0_1727418077932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/init_bert_ft_qqp_33_pipeline_en_5.5.0_3.0_1727418077932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("init_bert_ft_qqp_33_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("init_bert_ft_qqp_33_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|init_bert_ft_qqp_33_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/init_bert_ft_qqp-33 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-issue_classification_tweets_en.md b/docs/_posts/ahmedlone127/2024-09-27-issue_classification_tweets_en.md new file mode 100644 index 00000000000000..bb5e2b285eb58d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-issue_classification_tweets_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English issue_classification_tweets BertForSequenceClassification from z-dickson +author: John Snow Labs +name: issue_classification_tweets +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`issue_classification_tweets` is a English model originally trained by z-dickson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/issue_classification_tweets_en_5.5.0_3.0_1727397234493.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/issue_classification_tweets_en_5.5.0_3.0_1727397234493.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("issue_classification_tweets","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("issue_classification_tweets", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|issue_classification_tweets| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/z-dickson/issue_classification_tweets \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-labse_for_agreement_en.md b/docs/_posts/ahmedlone127/2024-09-27-labse_for_agreement_en.md new file mode 100644 index 00000000000000..3f86d340948ad4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-labse_for_agreement_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English labse_for_agreement BertForSequenceClassification from cassiepowell +author: John Snow Labs +name: labse_for_agreement +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`labse_for_agreement` is a English model originally trained by cassiepowell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/labse_for_agreement_en_5.5.0_3.0_1727419034834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/labse_for_agreement_en_5.5.0_3.0_1727419034834.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("labse_for_agreement","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("labse_for_agreement", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|labse_for_agreement| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.8 GB| + +## References + +https://huggingface.co/cassiepowell/LaBSE-for-agreement \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-labse_for_agreement_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-labse_for_agreement_pipeline_en.md new file mode 100644 index 00000000000000..3ac67121109f09 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-labse_for_agreement_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English labse_for_agreement_pipeline pipeline BertForSequenceClassification from cassiepowell +author: John Snow Labs +name: labse_for_agreement_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`labse_for_agreement_pipeline` is a English model originally trained by cassiepowell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/labse_for_agreement_pipeline_en_5.5.0_3.0_1727419125466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/labse_for_agreement_pipeline_en_5.5.0_3.0_1727419125466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("labse_for_agreement_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("labse_for_agreement_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|labse_for_agreement_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.8 GB| + +## References + +https://huggingface.co/cassiepowell/LaBSE-for-agreement + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_en.md b/docs/_posts/ahmedlone127/2024-09-27-legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_en.md new file mode 100644 index 00000000000000..0bb845d8485281 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English legal_bert_samoan_gen1_large_summarized_defined_chuvash_3 BertForSequenceClassification from wiorz +author: John Snow Labs +name: legal_bert_samoan_gen1_large_summarized_defined_chuvash_3 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_samoan_gen1_large_summarized_defined_chuvash_3` is a English model originally trained by wiorz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_en_5.5.0_3.0_1727413332206.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_en_5.5.0_3.0_1727413332206.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("legal_bert_samoan_gen1_large_summarized_defined_chuvash_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("legal_bert_samoan_gen1_large_summarized_defined_chuvash_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_bert_samoan_gen1_large_summarized_defined_chuvash_3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/wiorz/legal_bert_sm_gen1_large_summarized_defined_cv_3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline_en.md new file mode 100644 index 00000000000000..6a041c7d97e561 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline pipeline BertForSequenceClassification from wiorz +author: John Snow Labs +name: legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline` is a English model originally trained by wiorz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline_en_5.5.0_3.0_1727413352657.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline_en_5.5.0_3.0_1727413352657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_bert_samoan_gen1_large_summarized_defined_chuvash_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/wiorz/legal_bert_sm_gen1_large_summarized_defined_cv_3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-lovelace_evaluator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-lovelace_evaluator_pipeline_en.md new file mode 100644 index 00000000000000..0aaf5fd2810b1d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-lovelace_evaluator_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lovelace_evaluator_pipeline pipeline BertForSequenceClassification from rjbownes +author: John Snow Labs +name: lovelace_evaluator_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lovelace_evaluator_pipeline` is a English model originally trained by rjbownes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lovelace_evaluator_pipeline_en_5.5.0_3.0_1727412709664.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lovelace_evaluator_pipeline_en_5.5.0_3.0_1727412709664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lovelace_evaluator_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lovelace_evaluator_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lovelace_evaluator_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/rjbownes/lovelace-evaluator + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-m_bert_base_cased_language_detection_en.md b/docs/_posts/ahmedlone127/2024-09-27-m_bert_base_cased_language_detection_en.md new file mode 100644 index 00000000000000..677f5bda2eb544 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-m_bert_base_cased_language_detection_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English m_bert_base_cased_language_detection BertForSequenceClassification from Manirathinam21 +author: John Snow Labs +name: m_bert_base_cased_language_detection +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`m_bert_base_cased_language_detection` is a English model originally trained by Manirathinam21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/m_bert_base_cased_language_detection_en_5.5.0_3.0_1727414345895.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/m_bert_base_cased_language_detection_en_5.5.0_3.0_1727414345895.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("m_bert_base_cased_language_detection","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("m_bert_base_cased_language_detection", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|m_bert_base_cased_language_detection| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Manirathinam21/M-Bert-base-cased-language-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-malayalam_codemixed_abusive_muril_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-malayalam_codemixed_abusive_muril_pipeline_en.md new file mode 100644 index 00000000000000..005d2a37f2ad97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-malayalam_codemixed_abusive_muril_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English malayalam_codemixed_abusive_muril_pipeline pipeline BertForSequenceClassification from Hate-speech-CNERG +author: John Snow Labs +name: malayalam_codemixed_abusive_muril_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`malayalam_codemixed_abusive_muril_pipeline` is a English model originally trained by Hate-speech-CNERG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malayalam_codemixed_abusive_muril_pipeline_en_5.5.0_3.0_1727404317951.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malayalam_codemixed_abusive_muril_pipeline_en_5.5.0_3.0_1727404317951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("malayalam_codemixed_abusive_muril_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("malayalam_codemixed_abusive_muril_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|malayalam_codemixed_abusive_muril_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|892.7 MB| + +## References + +https://huggingface.co/Hate-speech-CNERG/malayalam-codemixed-abusive-MuRIL + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-marathi_sentiment_political_tweets_pipeline_mr.md b/docs/_posts/ahmedlone127/2024-09-27-marathi_sentiment_political_tweets_pipeline_mr.md new file mode 100644 index 00000000000000..fe3288c5ec3f08 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-marathi_sentiment_political_tweets_pipeline_mr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Marathi marathi_sentiment_political_tweets_pipeline pipeline BertForSequenceClassification from l3cube-pune +author: John Snow Labs +name: marathi_sentiment_political_tweets_pipeline +date: 2024-09-27 +tags: [mr, open_source, pipeline, onnx] +task: Text Classification +language: mr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`marathi_sentiment_political_tweets_pipeline` is a Marathi model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/marathi_sentiment_political_tweets_pipeline_mr_5.5.0_3.0_1727406056283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/marathi_sentiment_political_tweets_pipeline_mr_5.5.0_3.0_1727406056283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("marathi_sentiment_political_tweets_pipeline", lang = "mr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("marathi_sentiment_political_tweets_pipeline", lang = "mr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|marathi_sentiment_political_tweets_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|mr| +|Size:|892.9 MB| + +## References + +https://huggingface.co/l3cube-pune/marathi-sentiment-political-tweets + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-mbti_classification_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-27-mbti_classification_bert_base_uncased_en.md new file mode 100644 index 00000000000000..b157830bddec5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-mbti_classification_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mbti_classification_bert_base_uncased BertForSequenceClassification from Shunian +author: John Snow Labs +name: mbti_classification_bert_base_uncased +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbti_classification_bert_base_uncased` is a English model originally trained by Shunian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbti_classification_bert_base_uncased_en_5.5.0_3.0_1727399172903.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbti_classification_bert_base_uncased_en_5.5.0_3.0_1727399172903.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("mbti_classification_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mbti_classification_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbti_classification_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Shunian/mbti-classification-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-mbti_classification_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-mbti_classification_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..484221b70ceb3a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-mbti_classification_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mbti_classification_bert_base_uncased_pipeline pipeline BertForSequenceClassification from Shunian +author: John Snow Labs +name: mbti_classification_bert_base_uncased_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbti_classification_bert_base_uncased_pipeline` is a English model originally trained by Shunian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbti_classification_bert_base_uncased_pipeline_en_5.5.0_3.0_1727399193941.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbti_classification_bert_base_uncased_pipeline_en_5.5.0_3.0_1727399193941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mbti_classification_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mbti_classification_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbti_classification_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Shunian/mbti-classification-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-mengzi_bert_base_fin_sse50_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-mengzi_bert_base_fin_sse50_pipeline_en.md new file mode 100644 index 00000000000000..a2b0f83dd6b2fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-mengzi_bert_base_fin_sse50_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mengzi_bert_base_fin_sse50_pipeline pipeline BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_sse50_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_sse50_pipeline` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_sse50_pipeline_en_5.5.0_3.0_1727409701890.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_sse50_pipeline_en_5.5.0_3.0_1727409701890.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mengzi_bert_base_fin_sse50_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mengzi_bert_base_fin_sse50_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_sse50_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-SSE50 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-mental_health_classification_v0_1_en.md b/docs/_posts/ahmedlone127/2024-09-27-mental_health_classification_v0_1_en.md new file mode 100644 index 00000000000000..2d52675e6e2557 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-mental_health_classification_v0_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mental_health_classification_v0_1 BertForSequenceClassification from tahaenesaslanturk +author: John Snow Labs +name: mental_health_classification_v0_1 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_health_classification_v0_1` is a English model originally trained by tahaenesaslanturk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mental_health_classification_v0_1_en_5.5.0_3.0_1727416453652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mental_health_classification_v0_1_en_5.5.0_3.0_1727416453652.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("mental_health_classification_v0_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mental_health_classification_v0_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mental_health_classification_v0_1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tahaenesaslanturk/mental-health-classification-v0.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-mental_health_classification_v0_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-mental_health_classification_v0_1_pipeline_en.md new file mode 100644 index 00000000000000..adcfcc93f705f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-mental_health_classification_v0_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mental_health_classification_v0_1_pipeline pipeline BertForSequenceClassification from tahaenesaslanturk +author: John Snow Labs +name: mental_health_classification_v0_1_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mental_health_classification_v0_1_pipeline` is a English model originally trained by tahaenesaslanturk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mental_health_classification_v0_1_pipeline_en_5.5.0_3.0_1727416474296.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mental_health_classification_v0_1_pipeline_en_5.5.0_3.0_1727416474296.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mental_health_classification_v0_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mental_health_classification_v0_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mental_health_classification_v0_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/tahaenesaslanturk/mental-health-classification-v0.1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-miread_neuro_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-miread_neuro_pipeline_en.md new file mode 100644 index 00000000000000..67ec90748d2f6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-miread_neuro_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English miread_neuro_pipeline pipeline BertForSequenceClassification from biodatlab +author: John Snow Labs +name: miread_neuro_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`miread_neuro_pipeline` is a English model originally trained by biodatlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/miread_neuro_pipeline_en_5.5.0_3.0_1727418912120.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/miread_neuro_pipeline_en_5.5.0_3.0_1727418912120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("miread_neuro_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("miread_neuro_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|miread_neuro_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.8 MB| + +## References + +https://huggingface.co/biodatlab/MIReAD-Neuro + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-misinformation_covid_bert_base_chinese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-misinformation_covid_bert_base_chinese_pipeline_en.md new file mode 100644 index 00000000000000..6b96d07181d935 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-misinformation_covid_bert_base_chinese_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English misinformation_covid_bert_base_chinese_pipeline pipeline BertForSequenceClassification from Ghunghru +author: John Snow Labs +name: misinformation_covid_bert_base_chinese_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`misinformation_covid_bert_base_chinese_pipeline` is a English model originally trained by Ghunghru. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/misinformation_covid_bert_base_chinese_pipeline_en_5.5.0_3.0_1727409825742.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/misinformation_covid_bert_base_chinese_pipeline_en_5.5.0_3.0_1727409825742.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("misinformation_covid_bert_base_chinese_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("misinformation_covid_bert_base_chinese_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|misinformation_covid_bert_base_chinese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/Ghunghru/Misinformation-Covid-bert-base-chinese + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-mm05_pc_en.md b/docs/_posts/ahmedlone127/2024-09-27-mm05_pc_en.md new file mode 100644 index 00000000000000..9b6bbbd6ee7a83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-mm05_pc_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mm05_pc BertForSequenceClassification from Anwaarma +author: John Snow Labs +name: mm05_pc +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mm05_pc` is a English model originally trained by Anwaarma. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mm05_pc_en_5.5.0_3.0_1727415147877.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mm05_pc_en_5.5.0_3.0_1727415147877.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("mm05_pc","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mm05_pc", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mm05_pc| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Anwaarma/MM05-PC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-model_all_en.md b/docs/_posts/ahmedlone127/2024-09-27-model_all_en.md new file mode 100644 index 00000000000000..03f157a690bcc2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-model_all_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English model_all BertForSequenceClassification from irenema +author: John Snow Labs +name: model_all +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_all` is a English model originally trained by irenema. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_all_en_5.5.0_3.0_1727399619770.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_all_en_5.5.0_3.0_1727399619770.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("model_all","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model_all", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_all| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/irenema/model_all \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-model_all_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-model_all_pipeline_en.md new file mode 100644 index 00000000000000..17bafd3806e854 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-model_all_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English model_all_pipeline pipeline BertForSequenceClassification from irenema +author: John Snow Labs +name: model_all_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model_all_pipeline` is a English model originally trained by irenema. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model_all_pipeline_en_5.5.0_3.0_1727399655078.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model_all_pipeline_en_5.5.0_3.0_1727399655078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("model_all_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("model_all_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model_all_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/irenema/model_all + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-models_bert_1715968958_8824_en.md b/docs/_posts/ahmedlone127/2024-09-27-models_bert_1715968958_8824_en.md new file mode 100644 index 00000000000000..bb32aba4f09a1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-models_bert_1715968958_8824_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English models_bert_1715968958_8824 BertForSequenceClassification from llag9810 +author: John Snow Labs +name: models_bert_1715968958_8824 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`models_bert_1715968958_8824` is a English model originally trained by llag9810. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/models_bert_1715968958_8824_en_5.5.0_3.0_1727411358839.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/models_bert_1715968958_8824_en_5.5.0_3.0_1727411358839.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("models_bert_1715968958_8824","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("models_bert_1715968958_8824", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|models_bert_1715968958_8824| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/llag9810/Models-BERT-1715968958.8824 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-models_bert_1715968958_8824_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-models_bert_1715968958_8824_pipeline_en.md new file mode 100644 index 00000000000000..5e8a22df576cd8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-models_bert_1715968958_8824_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English models_bert_1715968958_8824_pipeline pipeline BertForSequenceClassification from llag9810 +author: John Snow Labs +name: models_bert_1715968958_8824_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`models_bert_1715968958_8824_pipeline` is a English model originally trained by llag9810. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/models_bert_1715968958_8824_pipeline_en_5.5.0_3.0_1727411390492.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/models_bert_1715968958_8824_pipeline_en_5.5.0_3.0_1727411390492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("models_bert_1715968958_8824_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("models_bert_1715968958_8824_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|models_bert_1715968958_8824_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/llag9810/Models-BERT-1715968958.8824 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-moodmeter_sentimental_analysis_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-moodmeter_sentimental_analysis_pipeline_en.md new file mode 100644 index 00000000000000..408a63edd0d3b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-moodmeter_sentimental_analysis_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English moodmeter_sentimental_analysis_pipeline pipeline BertForSequenceClassification from Priyanshuchaudhary2425 +author: John Snow Labs +name: moodmeter_sentimental_analysis_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`moodmeter_sentimental_analysis_pipeline` is a English model originally trained by Priyanshuchaudhary2425. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/moodmeter_sentimental_analysis_pipeline_en_5.5.0_3.0_1727398477236.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/moodmeter_sentimental_analysis_pipeline_en_5.5.0_3.0_1727398477236.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("moodmeter_sentimental_analysis_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("moodmeter_sentimental_analysis_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|moodmeter_sentimental_analysis_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Priyanshuchaudhary2425/MoodMeter-sentimental-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-n_bert_agnews_padding50model_en.md b/docs/_posts/ahmedlone127/2024-09-27-n_bert_agnews_padding50model_en.md new file mode 100644 index 00000000000000..1ad3a5333beb7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-n_bert_agnews_padding50model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_agnews_padding50model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_agnews_padding50model +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_agnews_padding50model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding50model_en_5.5.0_3.0_1727413764279.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding50model_en_5.5.0_3.0_1727413764279.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("n_bert_agnews_padding50model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_agnews_padding50model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_agnews_padding50model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Realgon/N_bert_agnews_padding50model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-n_bert_agnews_padding50model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-n_bert_agnews_padding50model_pipeline_en.md new file mode 100644 index 00000000000000..98acce3742c096 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-n_bert_agnews_padding50model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_bert_agnews_padding50model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_agnews_padding50model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_agnews_padding50model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding50model_pipeline_en_5.5.0_3.0_1727413785336.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_agnews_padding50model_pipeline_en_5.5.0_3.0_1727413785336.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_bert_agnews_padding50model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_bert_agnews_padding50model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_agnews_padding50model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Realgon/N_bert_agnews_padding50model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding30model_en.md b/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding30model_en.md new file mode 100644 index 00000000000000..32a2e1ddc88d39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding30model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_imdb_padding30model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_imdb_padding30model +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_imdb_padding30model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding30model_en_5.5.0_3.0_1727398229414.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding30model_en_5.5.0_3.0_1727398229414.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("n_bert_imdb_padding30model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_imdb_padding30model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_imdb_padding30model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Realgon/N_bert_imdb_padding30model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding30model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding30model_pipeline_en.md new file mode 100644 index 00000000000000..97d830ecb17b1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding30model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_bert_imdb_padding30model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_imdb_padding30model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_imdb_padding30model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding30model_pipeline_en_5.5.0_3.0_1727398251025.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding30model_pipeline_en_5.5.0_3.0_1727398251025.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_bert_imdb_padding30model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_bert_imdb_padding30model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_imdb_padding30model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Realgon/N_bert_imdb_padding30model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding60model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding60model_pipeline_en.md new file mode 100644 index 00000000000000..c247764d025be6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding60model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_bert_imdb_padding60model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_imdb_padding60model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_imdb_padding60model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding60model_pipeline_en_5.5.0_3.0_1727404816661.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding60model_pipeline_en_5.5.0_3.0_1727404816661.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_bert_imdb_padding60model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_bert_imdb_padding60model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_imdb_padding60model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Realgon/N_bert_imdb_padding60model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding90model_en.md b/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding90model_en.md new file mode 100644 index 00000000000000..9c4db2d4289fef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-n_bert_imdb_padding90model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_imdb_padding90model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_imdb_padding90model +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_imdb_padding90model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding90model_en_5.5.0_3.0_1727398981855.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_imdb_padding90model_en_5.5.0_3.0_1727398981855.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("n_bert_imdb_padding90model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_imdb_padding90model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_imdb_padding90model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/Realgon/N_bert_imdb_padding90model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-n_bert_sst5_padding20model_en.md b/docs/_posts/ahmedlone127/2024-09-27-n_bert_sst5_padding20model_en.md new file mode 100644 index 00000000000000..b26e6b378b6b9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-n_bert_sst5_padding20model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English n_bert_sst5_padding20model BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_sst5_padding20model +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_sst5_padding20model` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding20model_en_5.5.0_3.0_1727417376834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding20model_en_5.5.0_3.0_1727417376834.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("n_bert_sst5_padding20model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("n_bert_sst5_padding20model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_sst5_padding20model| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Realgon/N_bert_sst5_padding20model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-n_bert_sst5_padding20model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-n_bert_sst5_padding20model_pipeline_en.md new file mode 100644 index 00000000000000..17d28ff3f26a07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-n_bert_sst5_padding20model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English n_bert_sst5_padding20model_pipeline pipeline BertForSequenceClassification from Realgon +author: John Snow Labs +name: n_bert_sst5_padding20model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`n_bert_sst5_padding20model_pipeline` is a English model originally trained by Realgon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding20model_pipeline_en_5.5.0_3.0_1727417397865.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/n_bert_sst5_padding20model_pipeline_en_5.5.0_3.0_1727417397865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("n_bert_sst5_padding20model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("n_bert_sst5_padding20model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|n_bert_sst5_padding20model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/Realgon/N_bert_sst5_padding20model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-news_ranking_ft_bert_en.md b/docs/_posts/ahmedlone127/2024-09-27-news_ranking_ft_bert_en.md new file mode 100644 index 00000000000000..c13218dbc73322 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-news_ranking_ft_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English news_ranking_ft_bert BertForSequenceClassification from cmunhozc +author: John Snow Labs +name: news_ranking_ft_bert +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`news_ranking_ft_bert` is a English model originally trained by cmunhozc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/news_ranking_ft_bert_en_5.5.0_3.0_1727410119250.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/news_ranking_ft_bert_en_5.5.0_3.0_1727410119250.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("news_ranking_ft_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("news_ranking_ft_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|news_ranking_ft_bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/cmunhozc/news-ranking-ft-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-news_ranking_ft_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-news_ranking_ft_bert_pipeline_en.md new file mode 100644 index 00000000000000..ecb8ba2623ec82 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-news_ranking_ft_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English news_ranking_ft_bert_pipeline pipeline BertForSequenceClassification from cmunhozc +author: John Snow Labs +name: news_ranking_ft_bert_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`news_ranking_ft_bert_pipeline` is a English model originally trained by cmunhozc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/news_ranking_ft_bert_pipeline_en_5.5.0_3.0_1727410139484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/news_ranking_ft_bert_pipeline_en_5.5.0_3.0_1727410139484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("news_ranking_ft_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("news_ranking_ft_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|news_ranking_ft_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/cmunhozc/news-ranking-ft-bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-nhs_binary_class_en.md b/docs/_posts/ahmedlone127/2024-09-27-nhs_binary_class_en.md new file mode 100644 index 00000000000000..b0bab12c7f9dfe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-nhs_binary_class_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nhs_binary_class BertForSequenceClassification from intermezzo672 +author: John Snow Labs +name: nhs_binary_class +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nhs_binary_class` is a English model originally trained by intermezzo672. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nhs_binary_class_en_5.5.0_3.0_1727416328451.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nhs_binary_class_en_5.5.0_3.0_1727416328451.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("nhs_binary_class","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("nhs_binary_class", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nhs_binary_class| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.3 MB| + +## References + +https://huggingface.co/intermezzo672/NHS-binary-class \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-nlp_at_home_en.md b/docs/_posts/ahmedlone127/2024-09-27-nlp_at_home_en.md new file mode 100644 index 00000000000000..74197b4865ac0a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-nlp_at_home_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nlp_at_home BertForSequenceClassification from TeamNL +author: John Snow Labs +name: nlp_at_home +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_at_home` is a English model originally trained by TeamNL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_at_home_en_5.5.0_3.0_1727416822400.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_at_home_en_5.5.0_3.0_1727416822400.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("nlp_at_home","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("nlp_at_home", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_at_home| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|630.8 MB| + +## References + +https://huggingface.co/TeamNL/NLP-at-home \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-nlp_at_home_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-nlp_at_home_pipeline_en.md new file mode 100644 index 00000000000000..e0586062c4194a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-nlp_at_home_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nlp_at_home_pipeline pipeline BertForSequenceClassification from TeamNL +author: John Snow Labs +name: nlp_at_home_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_at_home_pipeline` is a English model originally trained by TeamNL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_at_home_pipeline_en_5.5.0_3.0_1727416853304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_at_home_pipeline_en_5.5.0_3.0_1727416853304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nlp_at_home_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nlp_at_home_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_at_home_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|630.8 MB| + +## References + +https://huggingface.co/TeamNL/NLP-at-home + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-norwegian_bokml_bert_base_sami_relevant_se.md b/docs/_posts/ahmedlone127/2024-09-27-norwegian_bokml_bert_base_sami_relevant_se.md new file mode 100644 index 00000000000000..99384e26076b8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-norwegian_bokml_bert_base_sami_relevant_se.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Northern Sami norwegian_bokml_bert_base_sami_relevant BertForSequenceClassification from NbAiLab +author: John Snow Labs +name: norwegian_bokml_bert_base_sami_relevant +date: 2024-09-27 +tags: [se, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: se +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_base_sami_relevant` is a Northern Sami model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_sami_relevant_se_5.5.0_3.0_1727404214550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_sami_relevant_se_5.5.0_3.0_1727404214550.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("norwegian_bokml_bert_base_sami_relevant","se") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norwegian_bokml_bert_base_sami_relevant", "se") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_bert_base_sami_relevant| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|se| +|Size:|668.4 MB| + +## References + +https://huggingface.co/NbAiLab/nb-bert-base-sami-relevant \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-notdiamond_4k_0001_xx.md b/docs/_posts/ahmedlone127/2024-09-27-notdiamond_4k_0001_xx.md new file mode 100644 index 00000000000000..e28c84b6b4fc56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-notdiamond_4k_0001_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual notdiamond_4k_0001 BertForSequenceClassification from arshadshk +author: John Snow Labs +name: notdiamond_4k_0001 +date: 2024-09-27 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`notdiamond_4k_0001` is a Multilingual model originally trained by arshadshk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/notdiamond_4k_0001_xx_5.5.0_3.0_1727419499518.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/notdiamond_4k_0001_xx_5.5.0_3.0_1727419499518.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("notdiamond_4k_0001","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("notdiamond_4k_0001", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|notdiamond_4k_0001| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|677.6 MB| + +## References + +https://huggingface.co/arshadshk/notdiamond-4k-0001 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-novel_genre_classification_bert_finetuned_en.md b/docs/_posts/ahmedlone127/2024-09-27-novel_genre_classification_bert_finetuned_en.md new file mode 100644 index 00000000000000..61f3e83e78d802 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-novel_genre_classification_bert_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English novel_genre_classification_bert_finetuned BertForSequenceClassification from Davida23 +author: John Snow Labs +name: novel_genre_classification_bert_finetuned +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`novel_genre_classification_bert_finetuned` is a English model originally trained by Davida23. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/novel_genre_classification_bert_finetuned_en_5.5.0_3.0_1727408332743.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/novel_genre_classification_bert_finetuned_en_5.5.0_3.0_1727408332743.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("novel_genre_classification_bert_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("novel_genre_classification_bert_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|novel_genre_classification_bert_finetuned| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Davida23/Novel_Genre_Classification_bert-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-olid_offensive_bert_multilingual_xx.md b/docs/_posts/ahmedlone127/2024-09-27-olid_offensive_bert_multilingual_xx.md new file mode 100644 index 00000000000000..00a69d95d9339a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-olid_offensive_bert_multilingual_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual olid_offensive_bert_multilingual BertForSequenceClassification from christinacdl +author: John Snow Labs +name: olid_offensive_bert_multilingual +date: 2024-09-27 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`olid_offensive_bert_multilingual` is a Multilingual model originally trained by christinacdl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/olid_offensive_bert_multilingual_xx_5.5.0_3.0_1727403153834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/olid_offensive_bert_multilingual_xx_5.5.0_3.0_1727403153834.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("olid_offensive_bert_multilingual","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("olid_offensive_bert_multilingual", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|olid_offensive_bert_multilingual| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/christinacdl/OLID_OFFENSIVE_BERT_MULTILINGUAL \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-output_ricocheh_en.md b/docs/_posts/ahmedlone127/2024-09-27-output_ricocheh_en.md new file mode 100644 index 00000000000000..2cdb2bc9366f2e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-output_ricocheh_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English output_ricocheh BertForSequenceClassification from RicoCHEH +author: John Snow Labs +name: output_ricocheh +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_ricocheh` is a English model originally trained by RicoCHEH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_ricocheh_en_5.5.0_3.0_1727414785971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_ricocheh_en_5.5.0_3.0_1727414785971.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("output_ricocheh","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("output_ricocheh", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|output_ricocheh| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/RicoCHEH/output \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-output_ricocheh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-output_ricocheh_pipeline_en.md new file mode 100644 index 00000000000000..7f6a9f73566446 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-output_ricocheh_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English output_ricocheh_pipeline pipeline BertForSequenceClassification from RicoCHEH +author: John Snow Labs +name: output_ricocheh_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`output_ricocheh_pipeline` is a English model originally trained by RicoCHEH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/output_ricocheh_pipeline_en_5.5.0_3.0_1727414807301.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/output_ricocheh_pipeline_en_5.5.0_3.0_1727414807301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("output_ricocheh_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("output_ricocheh_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|output_ricocheh_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/RicoCHEH/output + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-pan_2024_transformer_base_bert_base_cased_k2_en.md b/docs/_posts/ahmedlone127/2024-09-27-pan_2024_transformer_base_bert_base_cased_k2_en.md new file mode 100644 index 00000000000000..6222598c0ede69 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-pan_2024_transformer_base_bert_base_cased_k2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English pan_2024_transformer_base_bert_base_cased_k2 BertForSequenceClassification from dtorber +author: John Snow Labs +name: pan_2024_transformer_base_bert_base_cased_k2 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pan_2024_transformer_base_bert_base_cased_k2` is a English model originally trained by dtorber. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pan_2024_transformer_base_bert_base_cased_k2_en_5.5.0_3.0_1727416090064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pan_2024_transformer_base_bert_base_cased_k2_en_5.5.0_3.0_1727416090064.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("pan_2024_transformer_base_bert_base_cased_k2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("pan_2024_transformer_base_bert_base_cased_k2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pan_2024_transformer_base_bert_base_cased_k2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/dtorber/PAN-2024-transformer-base_bert-base-cased_K2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-pan_2024_transformer_base_bert_base_cased_k2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-pan_2024_transformer_base_bert_base_cased_k2_pipeline_en.md new file mode 100644 index 00000000000000..f7f72932b7b97e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-pan_2024_transformer_base_bert_base_cased_k2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English pan_2024_transformer_base_bert_base_cased_k2_pipeline pipeline BertForSequenceClassification from dtorber +author: John Snow Labs +name: pan_2024_transformer_base_bert_base_cased_k2_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pan_2024_transformer_base_bert_base_cased_k2_pipeline` is a English model originally trained by dtorber. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pan_2024_transformer_base_bert_base_cased_k2_pipeline_en_5.5.0_3.0_1727416110668.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pan_2024_transformer_base_bert_base_cased_k2_pipeline_en_5.5.0_3.0_1727416110668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pan_2024_transformer_base_bert_base_cased_k2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pan_2024_transformer_base_bert_base_cased_k2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pan_2024_transformer_base_bert_base_cased_k2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/dtorber/PAN-2024-transformer-base_bert-base-cased_K2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_fredriko_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_fredriko_pipeline_en.md new file mode 100644 index 00000000000000..8276ac9ae13789 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_fredriko_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_fredriko_pipeline pipeline BertForSequenceClassification from fredriko +author: John Snow Labs +name: phrasebank_sentiment_analysis_fredriko_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_fredriko_pipeline` is a English model originally trained by fredriko. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_fredriko_pipeline_en_5.5.0_3.0_1727406260101.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_fredriko_pipeline_en_5.5.0_3.0_1727406260101.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_fredriko_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_fredriko_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_fredriko_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/fredriko/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_kallev_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_kallev_pipeline_en.md new file mode 100644 index 00000000000000..2cc9ee5b956f36 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_kallev_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_kallev_pipeline pipeline BertForSequenceClassification from KalleV +author: John Snow Labs +name: phrasebank_sentiment_analysis_kallev_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_kallev_pipeline` is a English model originally trained by KalleV. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_kallev_pipeline_en_5.5.0_3.0_1727407889713.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_kallev_pipeline_en_5.5.0_3.0_1727407889713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_kallev_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_kallev_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_kallev_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/KalleV/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_mankness_en.md b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_mankness_en.md new file mode 100644 index 00000000000000..d50cdb37e939a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_mankness_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_mankness BertForSequenceClassification from mankness +author: John Snow Labs +name: phrasebank_sentiment_analysis_mankness +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_mankness` is a English model originally trained by mankness. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_mankness_en_5.5.0_3.0_1727410593200.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_mankness_en_5.5.0_3.0_1727410593200.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("phrasebank_sentiment_analysis_mankness","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("phrasebank_sentiment_analysis_mankness", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_mankness| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mankness/phrasebank-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_mankness_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_mankness_pipeline_en.md new file mode 100644 index 00000000000000..5feeb94949f348 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_mankness_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_mankness_pipeline pipeline BertForSequenceClassification from mankness +author: John Snow Labs +name: phrasebank_sentiment_analysis_mankness_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_mankness_pipeline` is a English model originally trained by mankness. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_mankness_pipeline_en_5.5.0_3.0_1727410614436.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_mankness_pipeline_en_5.5.0_3.0_1727410614436.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_mankness_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_mankness_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_mankness_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mankness/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_neerajprad_en.md b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_neerajprad_en.md new file mode 100644 index 00000000000000..a62b206768fa39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_neerajprad_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_neerajprad BertForSequenceClassification from neerajprad +author: John Snow Labs +name: phrasebank_sentiment_analysis_neerajprad +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_neerajprad` is a English model originally trained by neerajprad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_neerajprad_en_5.5.0_3.0_1727417398712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_neerajprad_en_5.5.0_3.0_1727417398712.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("phrasebank_sentiment_analysis_neerajprad","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("phrasebank_sentiment_analysis_neerajprad", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_neerajprad| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/neerajprad/phrasebank-sentiment-analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_neerajprad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_neerajprad_pipeline_en.md new file mode 100644 index 00000000000000..d128558f4c187c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-phrasebank_sentiment_analysis_neerajprad_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English phrasebank_sentiment_analysis_neerajprad_pipeline pipeline BertForSequenceClassification from neerajprad +author: John Snow Labs +name: phrasebank_sentiment_analysis_neerajprad_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phrasebank_sentiment_analysis_neerajprad_pipeline` is a English model originally trained by neerajprad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_neerajprad_pipeline_en_5.5.0_3.0_1727417422729.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phrasebank_sentiment_analysis_neerajprad_pipeline_en_5.5.0_3.0_1727417422729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("phrasebank_sentiment_analysis_neerajprad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("phrasebank_sentiment_analysis_neerajprad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phrasebank_sentiment_analysis_neerajprad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/neerajprad/phrasebank-sentiment-analysis + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-popbert_pipeline_de.md b/docs/_posts/ahmedlone127/2024-09-27-popbert_pipeline_de.md new file mode 100644 index 00000000000000..cef11373d7f6ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-popbert_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German popbert_pipeline pipeline BertForSequenceClassification from luerhard +author: John Snow Labs +name: popbert_pipeline +date: 2024-09-27 +tags: [de, open_source, pipeline, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`popbert_pipeline` is a German model originally trained by luerhard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/popbert_pipeline_de_5.5.0_3.0_1727407201774.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/popbert_pipeline_de_5.5.0_3.0_1727407201774.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("popbert_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("popbert_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|popbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|1.3 GB| + +## References + +https://huggingface.co/luerhard/PopBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-pubmedbert_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-pubmedbert_qnli_pipeline_en.md new file mode 100644 index 00000000000000..49367c075f2a64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-pubmedbert_qnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English pubmedbert_qnli_pipeline pipeline BertForSequenceClassification from mervenoyan +author: John Snow Labs +name: pubmedbert_qnli_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubmedbert_qnli_pipeline` is a English model originally trained by mervenoyan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubmedbert_qnli_pipeline_en_5.5.0_3.0_1727408731079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubmedbert_qnli_pipeline_en_5.5.0_3.0_1727408731079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pubmedbert_qnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pubmedbert_qnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pubmedbert_qnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.4 MB| + +## References + +https://huggingface.co/mervenoyan/PubMedBERT-QNLI + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-qd_tweet_bert_base_turkish_en.md b/docs/_posts/ahmedlone127/2024-09-27-qd_tweet_bert_base_turkish_en.md new file mode 100644 index 00000000000000..a04eda87a1ff12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-qd_tweet_bert_base_turkish_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English qd_tweet_bert_base_turkish BertForSequenceClassification from Izzet +author: John Snow Labs +name: qd_tweet_bert_base_turkish +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qd_tweet_bert_base_turkish` is a English model originally trained by Izzet. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qd_tweet_bert_base_turkish_en_5.5.0_3.0_1727417889231.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qd_tweet_bert_base_turkish_en_5.5.0_3.0_1727417889231.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("qd_tweet_bert_base_turkish","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("qd_tweet_bert_base_turkish", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qd_tweet_bert_base_turkish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|691.2 MB| + +## References + +https://huggingface.co/Izzet/qd_tweet_bert-base-turkish \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-qp_mscoco_sbert_lr5e_5_en.md b/docs/_posts/ahmedlone127/2024-09-27-qp_mscoco_sbert_lr5e_5_en.md new file mode 100644 index 00000000000000..eae53855511790 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-qp_mscoco_sbert_lr5e_5_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English qp_mscoco_sbert_lr5e_5 BertForSequenceClassification from madhavsankar +author: John Snow Labs +name: qp_mscoco_sbert_lr5e_5 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qp_mscoco_sbert_lr5e_5` is a English model originally trained by madhavsankar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qp_mscoco_sbert_lr5e_5_en_5.5.0_3.0_1727415967497.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qp_mscoco_sbert_lr5e_5_en_5.5.0_3.0_1727415967497.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("qp_mscoco_sbert_lr5e_5","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("qp_mscoco_sbert_lr5e_5", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qp_mscoco_sbert_lr5e_5| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.2 MB| + +## References + +https://huggingface.co/madhavsankar/qp-mscoco-sbert-lr5e-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-romanian_sentiment_01_en.md b/docs/_posts/ahmedlone127/2024-09-27-romanian_sentiment_01_en.md new file mode 100644 index 00000000000000..d7ed5fa1b2e9aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-romanian_sentiment_01_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English romanian_sentiment_01 BertForSequenceClassification from andyP +author: John Snow Labs +name: romanian_sentiment_01 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`romanian_sentiment_01` is a English model originally trained by andyP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/romanian_sentiment_01_en_5.5.0_3.0_1727418722480.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/romanian_sentiment_01_en_5.5.0_3.0_1727418722480.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("romanian_sentiment_01","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("romanian_sentiment_01", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|romanian_sentiment_01| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|431.4 MB| + +## References + +https://huggingface.co/andyP/ro-sentiment-01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-romanian_sentiment_01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-romanian_sentiment_01_pipeline_en.md new file mode 100644 index 00000000000000..99d427a51d9cc8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-romanian_sentiment_01_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English romanian_sentiment_01_pipeline pipeline BertForSequenceClassification from andyP +author: John Snow Labs +name: romanian_sentiment_01_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`romanian_sentiment_01_pipeline` is a English model originally trained by andyP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/romanian_sentiment_01_pipeline_en_5.5.0_3.0_1727418745176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/romanian_sentiment_01_pipeline_en_5.5.0_3.0_1727418745176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("romanian_sentiment_01_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("romanian_sentiment_01_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|romanian_sentiment_01_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|431.5 MB| + +## References + +https://huggingface.co/andyP/ro-sentiment-01 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-rubert_tiny2_clf_ru.md b/docs/_posts/ahmedlone127/2024-09-27-rubert_tiny2_clf_ru.md new file mode 100644 index 00000000000000..ca34fe07326d5a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-rubert_tiny2_clf_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian rubert_tiny2_clf BertForSequenceClassification from r1char9 +author: John Snow Labs +name: rubert_tiny2_clf +date: 2024-09-27 +tags: [ru, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: ru +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_tiny2_clf` is a Russian model originally trained by r1char9. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny2_clf_ru_5.5.0_3.0_1727416759320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny2_clf_ru_5.5.0_3.0_1727416759320.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("rubert_tiny2_clf","ru") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_tiny2_clf", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_tiny2_clf| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|109.5 MB| + +## References + +https://huggingface.co/r1char9/rubert-tiny2-clf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-russian_evasiveness_en.md b/docs/_posts/ahmedlone127/2024-09-27-russian_evasiveness_en.md new file mode 100644 index 00000000000000..de8620e34efdc3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-russian_evasiveness_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English russian_evasiveness BertForSequenceClassification from alenaa +author: John Snow Labs +name: russian_evasiveness +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`russian_evasiveness` is a English model originally trained by alenaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/russian_evasiveness_en_5.5.0_3.0_1727411756076.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/russian_evasiveness_en_5.5.0_3.0_1727411756076.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("russian_evasiveness","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("russian_evasiveness", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|russian_evasiveness| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|666.5 MB| + +## References + +https://huggingface.co/alenaa/ru_evasiveness \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-russian_evasiveness_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-russian_evasiveness_pipeline_en.md new file mode 100644 index 00000000000000..1a6c01cb96dce6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-russian_evasiveness_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English russian_evasiveness_pipeline pipeline BertForSequenceClassification from alenaa +author: John Snow Labs +name: russian_evasiveness_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`russian_evasiveness_pipeline` is a English model originally trained by alenaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/russian_evasiveness_pipeline_en_5.5.0_3.0_1727411789601.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/russian_evasiveness_pipeline_en_5.5.0_3.0_1727411789601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("russian_evasiveness_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("russian_evasiveness_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|russian_evasiveness_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|666.5 MB| + +## References + +https://huggingface.co/alenaa/ru_evasiveness + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sagemaker_bert_mini_arabic_arsas_en.md b/docs/_posts/ahmedlone127/2024-09-27-sagemaker_bert_mini_arabic_arsas_en.md new file mode 100644 index 00000000000000..ae1d4fbe821a87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sagemaker_bert_mini_arabic_arsas_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sagemaker_bert_mini_arabic_arsas BertForSequenceClassification from Osaleh +author: John Snow Labs +name: sagemaker_bert_mini_arabic_arsas +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sagemaker_bert_mini_arabic_arsas` is a English model originally trained by Osaleh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sagemaker_bert_mini_arabic_arsas_en_5.5.0_3.0_1727412116277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sagemaker_bert_mini_arabic_arsas_en_5.5.0_3.0_1727412116277.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("sagemaker_bert_mini_arabic_arsas","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sagemaker_bert_mini_arabic_arsas", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sagemaker_bert_mini_arabic_arsas| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|43.6 MB| + +## References + +https://huggingface.co/Osaleh/sagemaker-bert-mini-arabic-ArSAS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sagemaker_bert_mini_arabic_arsas_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-sagemaker_bert_mini_arabic_arsas_pipeline_en.md new file mode 100644 index 00000000000000..10ed2b5fe0d11c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sagemaker_bert_mini_arabic_arsas_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sagemaker_bert_mini_arabic_arsas_pipeline pipeline BertForSequenceClassification from Osaleh +author: John Snow Labs +name: sagemaker_bert_mini_arabic_arsas_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sagemaker_bert_mini_arabic_arsas_pipeline` is a English model originally trained by Osaleh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sagemaker_bert_mini_arabic_arsas_pipeline_en_5.5.0_3.0_1727412118711.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sagemaker_bert_mini_arabic_arsas_pipeline_en_5.5.0_3.0_1727412118711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sagemaker_bert_mini_arabic_arsas_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sagemaker_bert_mini_arabic_arsas_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sagemaker_bert_mini_arabic_arsas_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|43.6 MB| + +## References + +https://huggingface.co/Osaleh/sagemaker-bert-mini-arabic-ArSAS + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..0c63c16dab2ab7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline pipeline BertForSequenceClassification from haryoaw +author: John Snow Labs +name: scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline` is a English model originally trained by haryoaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727404484925.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727404484925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_tcr_data_glue_cola_model_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/haryoaw/scenario-TCR-data-glue-cola-model-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_mrpc_model_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_mrpc_model_bert_base_uncased_en.md new file mode 100644 index 00000000000000..8489d08713f170 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_mrpc_model_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English scenario_tcr_data_glue_mrpc_model_bert_base_uncased BertForSequenceClassification from haryoaw +author: John Snow Labs +name: scenario_tcr_data_glue_mrpc_model_bert_base_uncased +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_glue_mrpc_model_bert_base_uncased` is a English model originally trained by haryoaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_mrpc_model_bert_base_uncased_en_5.5.0_3.0_1727400765495.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_mrpc_model_bert_base_uncased_en_5.5.0_3.0_1727400765495.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("scenario_tcr_data_glue_mrpc_model_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scenario_tcr_data_glue_mrpc_model_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_tcr_data_glue_mrpc_model_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/haryoaw/scenario-TCR-data-glue-mrpc-model-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..8b697b5c86f9ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline pipeline BertForSequenceClassification from haryoaw +author: John Snow Labs +name: scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline` is a English model originally trained by haryoaw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727400786241.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline_en_5.5.0_3.0_1727400786241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_tcr_data_glue_mrpc_model_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/haryoaw/scenario-TCR-data-glue-mrpc-model-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sead_l_6_h_384_a_12_qnli_en.md b/docs/_posts/ahmedlone127/2024-09-27-sead_l_6_h_384_a_12_qnli_en.md new file mode 100644 index 00000000000000..86ff9cbdb5eed4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sead_l_6_h_384_a_12_qnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sead_l_6_h_384_a_12_qnli BertForSequenceClassification from C5i +author: John Snow Labs +name: sead_l_6_h_384_a_12_qnli +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sead_l_6_h_384_a_12_qnli` is a English model originally trained by C5i. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sead_l_6_h_384_a_12_qnli_en_5.5.0_3.0_1727400490544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sead_l_6_h_384_a_12_qnli_en_5.5.0_3.0_1727400490544.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("sead_l_6_h_384_a_12_qnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sead_l_6_h_384_a_12_qnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sead_l_6_h_384_a_12_qnli| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|84.3 MB| + +## References + +https://huggingface.co/C5i/SEAD-L-6_H-384_A-12-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline_en.md new file mode 100644 index 00000000000000..a4e9318fea8f15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline pipeline BertForSequenceClassification from Dwaraka +author: John Snow Labs +name: sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline` is a English model originally trained by Dwaraka. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline_en_5.5.0_3.0_1727413139011.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline_en_5.5.0_3.0_1727413139011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_classification_cola_bert_base_uncased_encoder_only_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Dwaraka/Sentence_Classification_CoLA_BERT_base_uncased_Encoder_Only_Model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_en.md b/docs/_posts/ahmedlone127/2024-09-27-sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_en.md new file mode 100644 index 00000000000000..1841b7433d8cb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment BertForSequenceClassification from Theivaprakasham +author: John Snow Labs +name: sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_transformers_paraphrase_minilm_l6_v2_twitter_sentiment` is a English model originally trained by Theivaprakasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_en_5.5.0_3.0_1727406788029.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_en_5.5.0_3.0_1727406788029.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("sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|84.6 MB| + +## References + +https://huggingface.co/Theivaprakasham/sentence-transformers-paraphrase-MiniLM-L6-v2-twitter_sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline_en.md new file mode 100644 index 00000000000000..acc2dc6c29505d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline pipeline BertForSequenceClassification from Theivaprakasham +author: John Snow Labs +name: sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline` is a English model originally trained by Theivaprakasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline_en_5.5.0_3.0_1727406792191.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline_en_5.5.0_3.0_1727406792191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_transformers_paraphrase_minilm_l6_v2_twitter_sentiment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|84.7 MB| + +## References + +https://huggingface.co/Theivaprakasham/sentence-transformers-paraphrase-MiniLM-L6-v2-twitter_sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sentense_pairs_cls_en.md b/docs/_posts/ahmedlone127/2024-09-27-sentense_pairs_cls_en.md new file mode 100644 index 00000000000000..da73d82ad89974 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sentense_pairs_cls_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentense_pairs_cls BertForSequenceClassification from Eitanli +author: John Snow Labs +name: sentense_pairs_cls +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentense_pairs_cls` is a English model originally trained by Eitanli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentense_pairs_cls_en_5.5.0_3.0_1727409940599.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentense_pairs_cls_en_5.5.0_3.0_1727409940599.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("sentense_pairs_cls","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentense_pairs_cls", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentense_pairs_cls| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Eitanli/sentense_pairs_cls \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sentense_pairs_cls_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-sentense_pairs_cls_pipeline_en.md new file mode 100644 index 00000000000000..25687744c0bc33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sentense_pairs_cls_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentense_pairs_cls_pipeline pipeline BertForSequenceClassification from Eitanli +author: John Snow Labs +name: sentense_pairs_cls_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentense_pairs_cls_pipeline` is a English model originally trained by Eitanli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentense_pairs_cls_pipeline_en_5.5.0_3.0_1727409961920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentense_pairs_cls_pipeline_en_5.5.0_3.0_1727409961920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentense_pairs_cls_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentense_pairs_cls_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentense_pairs_cls_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Eitanli/sentense_pairs_cls + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sentiment_analysis_french_en.md b/docs/_posts/ahmedlone127/2024-09-27-sentiment_analysis_french_en.md new file mode 100644 index 00000000000000..0be168b4bbdc9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sentiment_analysis_french_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentiment_analysis_french BertForSequenceClassification from serge-wilson +author: John Snow Labs +name: sentiment_analysis_french +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_analysis_french` is a English model originally trained by serge-wilson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_analysis_french_en_5.5.0_3.0_1727398947565.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_analysis_french_en_5.5.0_3.0_1727398947565.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("sentiment_analysis_french","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_analysis_french", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_analysis_french| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/serge-wilson/sentiment_analysis_french \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-sentimentanalysis_beto_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-sentimentanalysis_beto_pipeline_en.md new file mode 100644 index 00000000000000..3f56fc7dd0b928 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-sentimentanalysis_beto_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentimentanalysis_beto_pipeline pipeline BertForSequenceClassification from tr3cks +author: John Snow Labs +name: sentimentanalysis_beto_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentimentanalysis_beto_pipeline` is a English model originally trained by tr3cks. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentimentanalysis_beto_pipeline_en_5.5.0_3.0_1727400556878.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentimentanalysis_beto_pipeline_en_5.5.0_3.0_1727400556878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentimentanalysis_beto_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentimentanalysis_beto_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentimentanalysis_beto_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/tr3cks/SentimentAnalysis_BETO + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-ssclass_best_en.md b/docs/_posts/ahmedlone127/2024-09-27-ssclass_best_en.md new file mode 100644 index 00000000000000..b0a0fa161b1019 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-ssclass_best_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ssclass_best BertForSequenceClassification from asaderu-ai +author: John Snow Labs +name: ssclass_best +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ssclass_best` is a English model originally trained by asaderu-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ssclass_best_en_5.5.0_3.0_1727410425031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ssclass_best_en_5.5.0_3.0_1727410425031.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("ssclass_best","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ssclass_best", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ssclass_best| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.8 MB| + +## References + +https://huggingface.co/asaderu-ai/ssclass_best \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-ssclass_best_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-ssclass_best_pipeline_en.md new file mode 100644 index 00000000000000..3f184f272b4f34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-ssclass_best_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ssclass_best_pipeline pipeline BertForSequenceClassification from asaderu-ai +author: John Snow Labs +name: ssclass_best_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ssclass_best_pipeline` is a English model originally trained by asaderu-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ssclass_best_pipeline_en_5.5.0_3.0_1727410449512.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ssclass_best_pipeline_en_5.5.0_3.0_1727410449512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ssclass_best_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ssclass_best_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ssclass_best_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.8 MB| + +## References + +https://huggingface.co/asaderu-ai/ssclass_best + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-swissfinbert_v3_en.md b/docs/_posts/ahmedlone127/2024-09-27-swissfinbert_v3_en.md new file mode 100644 index 00000000000000..28d133f98f1f5d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-swissfinbert_v3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English swissfinbert_v3 BertForSequenceClassification from AlGatone21 +author: John Snow Labs +name: swissfinbert_v3 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swissfinbert_v3` is a English model originally trained by AlGatone21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swissfinbert_v3_en_5.5.0_3.0_1727402042965.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swissfinbert_v3_en_5.5.0_3.0_1727402042965.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("swissfinbert_v3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("swissfinbert_v3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|swissfinbert_v3| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/AlGatone21/SwissFinBERT_v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-test_hub_en.md b/docs/_posts/ahmedlone127/2024-09-27-test_hub_en.md new file mode 100644 index 00000000000000..1cece98e7941c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-test_hub_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English test_hub BertForSequenceClassification from xy4286 +author: John Snow Labs +name: test_hub +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_hub` is a English model originally trained by xy4286. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_hub_en_5.5.0_3.0_1727415926816.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_hub_en_5.5.0_3.0_1727415926816.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("test_hub","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("test_hub", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_hub| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/xy4286/test-hub \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-test_trainer_wennnny_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-test_trainer_wennnny_pipeline_en.md new file mode 100644 index 00000000000000..4dc4064ca2884b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-test_trainer_wennnny_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English test_trainer_wennnny_pipeline pipeline BertForSequenceClassification from wennnny +author: John Snow Labs +name: test_trainer_wennnny_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_trainer_wennnny_pipeline` is a English model originally trained by wennnny. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_trainer_wennnny_pipeline_en_5.5.0_3.0_1727416979846.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_trainer_wennnny_pipeline_en_5.5.0_3.0_1727416979846.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("test_trainer_wennnny_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("test_trainer_wennnny_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_trainer_wennnny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/wennnny/test-trainer + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-text_classifier_en.md b/docs/_posts/ahmedlone127/2024-09-27-text_classifier_en.md new file mode 100644 index 00000000000000..bcf1907753fbb5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-text_classifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English text_classifier BertForSequenceClassification from Pranavathejaswi +author: John Snow Labs +name: text_classifier +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`text_classifier` is a English model originally trained by Pranavathejaswi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/text_classifier_en_5.5.0_3.0_1727412671602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/text_classifier_en_5.5.0_3.0_1727412671602.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("text_classifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("text_classifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|text_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Pranavathejaswi/Text_Classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-the_misfits_en.md b/docs/_posts/ahmedlone127/2024-09-27-the_misfits_en.md new file mode 100644 index 00000000000000..ff45624deb8e3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-the_misfits_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English the_misfits BertForSequenceClassification from rpratap2102 +author: John Snow Labs +name: the_misfits +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`the_misfits` is a English model originally trained by rpratap2102. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/the_misfits_en_5.5.0_3.0_1727396327184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/the_misfits_en_5.5.0_3.0_1727396327184.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("the_misfits","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("the_misfits", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|the_misfits| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/rpratap2102/The_Misfits \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-the_misfits_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-the_misfits_pipeline_en.md new file mode 100644 index 00000000000000..f44956e0c34320 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-the_misfits_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English the_misfits_pipeline pipeline BertForSequenceClassification from rpratap2102 +author: John Snow Labs +name: the_misfits_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`the_misfits_pipeline` is a English model originally trained by rpratap2102. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/the_misfits_pipeline_en_5.5.0_3.0_1727396348727.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/the_misfits_pipeline_en_5.5.0_3.0_1727396348727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("the_misfits_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("the_misfits_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|the_misfits_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/rpratap2102/The_Misfits + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-thext_pce_czech_en.md b/docs/_posts/ahmedlone127/2024-09-27-thext_pce_czech_en.md new file mode 100644 index 00000000000000..55839bce8b6b18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-thext_pce_czech_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English thext_pce_czech BertForSequenceClassification from pietrocagnasso +author: John Snow Labs +name: thext_pce_czech +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_pce_czech` is a English model originally trained by pietrocagnasso. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thext_pce_czech_en_5.5.0_3.0_1727407214811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thext_pce_czech_en_5.5.0_3.0_1727407214811.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("thext_pce_czech","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("thext_pce_czech", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|thext_pce_czech| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.1 MB| + +## References + +https://huggingface.co/pietrocagnasso/thext-pce-cs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_ranker_bm25_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_ranker_bm25_pipeline_en.md new file mode 100644 index 00000000000000..af31fb5ab699de --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_ranker_bm25_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tiny_bert_ranker_bm25_pipeline pipeline BertForSequenceClassification from webis +author: John Snow Labs +name: tiny_bert_ranker_bm25_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_ranker_bm25_pipeline` is a English model originally trained by webis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_ranker_bm25_pipeline_en_5.5.0_3.0_1727415675191.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_ranker_bm25_pipeline_en_5.5.0_3.0_1727415675191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tiny_bert_ranker_bm25_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tiny_bert_ranker_bm25_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_ranker_bm25_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|16.8 MB| + +## References + +https://huggingface.co/webis/tiny-bert-ranker-bm25 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_sst2_distilled_hsuk_en.md b/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_sst2_distilled_hsuk_en.md new file mode 100644 index 00000000000000..e487e557de5bc1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_sst2_distilled_hsuk_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_hsuk BertForSequenceClassification from hsuk +author: John Snow Labs +name: tiny_bert_sst2_distilled_hsuk +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_hsuk` is a English model originally trained by hsuk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_hsuk_en_5.5.0_3.0_1727407867972.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_hsuk_en_5.5.0_3.0_1727407867972.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("tiny_bert_sst2_distilled_hsuk","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_hsuk", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_hsuk| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/hsuk/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_sst2_distilled_sukriti29_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_sst2_distilled_sukriti29_pipeline_en.md new file mode 100644 index 00000000000000..91a86ee2f1ebee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-tiny_bert_sst2_distilled_sukriti29_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_sukriti29_pipeline pipeline BertForSequenceClassification from Sukriti29 +author: John Snow Labs +name: tiny_bert_sst2_distilled_sukriti29_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_sukriti29_pipeline` is a English model originally trained by Sukriti29. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_sukriti29_pipeline_en_5.5.0_3.0_1727410625385.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_sukriti29_pipeline_en_5.5.0_3.0_1727410625385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tiny_bert_sst2_distilled_sukriti29_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tiny_bert_sst2_distilled_sukriti29_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_sukriti29_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|16.8 MB| + +## References + +https://huggingface.co/Sukriti29/tiny-bert-sst2-distilled + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-trac2020_iben_c_bert_base_multilingual_uncased_xx.md b/docs/_posts/ahmedlone127/2024-09-27-trac2020_iben_c_bert_base_multilingual_uncased_xx.md new file mode 100644 index 00000000000000..c61f1712791146 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-trac2020_iben_c_bert_base_multilingual_uncased_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual trac2020_iben_c_bert_base_multilingual_uncased BertForSequenceClassification from socialmediaie +author: John Snow Labs +name: trac2020_iben_c_bert_base_multilingual_uncased +date: 2024-09-27 +tags: [xx, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`trac2020_iben_c_bert_base_multilingual_uncased` is a Multilingual model originally trained by socialmediaie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/trac2020_iben_c_bert_base_multilingual_uncased_xx_5.5.0_3.0_1727397131933.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/trac2020_iben_c_bert_base_multilingual_uncased_xx_5.5.0_3.0_1727397131933.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("trac2020_iben_c_bert_base_multilingual_uncased","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("trac2020_iben_c_bert_base_multilingual_uncased", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|trac2020_iben_c_bert_base_multilingual_uncased| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.8 MB| + +## References + +https://huggingface.co/socialmediaie/TRAC2020_IBEN_C_bert-base-multilingual-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-turkishmusiclyricsmodel_pipeline_tr.md b/docs/_posts/ahmedlone127/2024-09-27-turkishmusiclyricsmodel_pipeline_tr.md new file mode 100644 index 00000000000000..b1e6aadae0c714 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-turkishmusiclyricsmodel_pipeline_tr.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Turkish turkishmusiclyricsmodel_pipeline pipeline BertForSequenceClassification from YusufDagdeviren +author: John Snow Labs +name: turkishmusiclyricsmodel_pipeline +date: 2024-09-27 +tags: [tr, open_source, pipeline, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`turkishmusiclyricsmodel_pipeline` is a Turkish model originally trained by YusufDagdeviren. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/turkishmusiclyricsmodel_pipeline_tr_5.5.0_3.0_1727414814052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/turkishmusiclyricsmodel_pipeline_tr_5.5.0_3.0_1727414814052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("turkishmusiclyricsmodel_pipeline", lang = "tr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("turkishmusiclyricsmodel_pipeline", lang = "tr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|turkishmusiclyricsmodel_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|tr| +|Size:|414.5 MB| + +## References + +https://huggingface.co/YusufDagdeviren/turkishmusiclyricsmodel + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-tweetbasedsa_en.md b/docs/_posts/ahmedlone127/2024-09-27-tweetbasedsa_en.md new file mode 100644 index 00000000000000..8c043d5a556a4a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-tweetbasedsa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tweetbasedsa BertForSequenceClassification from DSI +author: John Snow Labs +name: tweetbasedsa +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweetbasedsa` is a English model originally trained by DSI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweetbasedsa_en_5.5.0_3.0_1727417829533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweetbasedsa_en_5.5.0_3.0_1727417829533.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("tweetbasedsa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tweetbasedsa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tweetbasedsa| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|610.9 MB| + +## References + +https://huggingface.co/DSI/TweetBasedSA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-v4_bert_text_classification_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-v4_bert_text_classification_model_pipeline_en.md new file mode 100644 index 00000000000000..fa6239735d5f47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-v4_bert_text_classification_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English v4_bert_text_classification_model_pipeline pipeline BertForSequenceClassification from AmirlyPhd +author: John Snow Labs +name: v4_bert_text_classification_model_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`v4_bert_text_classification_model_pipeline` is a English model originally trained by AmirlyPhd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/v4_bert_text_classification_model_pipeline_en_5.5.0_3.0_1727405595888.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/v4_bert_text_classification_model_pipeline_en_5.5.0_3.0_1727405595888.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("v4_bert_text_classification_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("v4_bert_text_classification_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|v4_bert_text_classification_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/AmirlyPhd/V4-bert-text-classification-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-va_bert_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-va_bert_classification_en.md new file mode 100644 index 00000000000000..bd4aebe54ace07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-va_bert_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English va_bert_classification BertForSequenceClassification from mschwab +author: John Snow Labs +name: va_bert_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`va_bert_classification` is a English model originally trained by mschwab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/va_bert_classification_en_5.5.0_3.0_1727397854857.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/va_bert_classification_en_5.5.0_3.0_1727397854857.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("va_bert_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("va_bert_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|va_bert_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/mschwab/va_bert_classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-va_bert_classification_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-va_bert_classification_pipeline_en.md new file mode 100644 index 00000000000000..b138b0eab21e01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-va_bert_classification_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English va_bert_classification_pipeline pipeline BertForSequenceClassification from mschwab +author: John Snow Labs +name: va_bert_classification_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`va_bert_classification_pipeline` is a English model originally trained by mschwab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/va_bert_classification_pipeline_en_5.5.0_3.0_1727397875612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/va_bert_classification_pipeline_en_5.5.0_3.0_1727397875612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("va_bert_classification_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("va_bert_classification_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|va_bert_classification_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/mschwab/va_bert_classification + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-valueeval24_bert_baseline_toy_2024_02_27_en.md b/docs/_posts/ahmedlone127/2024-09-27-valueeval24_bert_baseline_toy_2024_02_27_en.md new file mode 100644 index 00000000000000..2281ac6ea089e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-valueeval24_bert_baseline_toy_2024_02_27_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English valueeval24_bert_baseline_toy_2024_02_27 BertForSequenceClassification from JohannesKiesel +author: John Snow Labs +name: valueeval24_bert_baseline_toy_2024_02_27 +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`valueeval24_bert_baseline_toy_2024_02_27` is a English model originally trained by JohannesKiesel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/valueeval24_bert_baseline_toy_2024_02_27_en_5.5.0_3.0_1727402983341.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/valueeval24_bert_baseline_toy_2024_02_27_en_5.5.0_3.0_1727402983341.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("valueeval24_bert_baseline_toy_2024_02_27","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("valueeval24_bert_baseline_toy_2024_02_27", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|valueeval24_bert_baseline_toy_2024_02_27| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/JohannesKiesel/valueeval24-bert-baseline-toy-2024-02-27 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-valueeval24_bert_baseline_toy_2024_02_27_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-valueeval24_bert_baseline_toy_2024_02_27_pipeline_en.md new file mode 100644 index 00000000000000..96344d56abee98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-valueeval24_bert_baseline_toy_2024_02_27_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English valueeval24_bert_baseline_toy_2024_02_27_pipeline pipeline BertForSequenceClassification from JohannesKiesel +author: John Snow Labs +name: valueeval24_bert_baseline_toy_2024_02_27_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`valueeval24_bert_baseline_toy_2024_02_27_pipeline` is a English model originally trained by JohannesKiesel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/valueeval24_bert_baseline_toy_2024_02_27_pipeline_en_5.5.0_3.0_1727403006477.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/valueeval24_bert_baseline_toy_2024_02_27_pipeline_en_5.5.0_3.0_1727403006477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("valueeval24_bert_baseline_toy_2024_02_27_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("valueeval24_bert_baseline_toy_2024_02_27_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|valueeval24_bert_baseline_toy_2024_02_27_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/JohannesKiesel/valueeval24-bert-baseline-toy-2024-02-27 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-vietnamese_poem_classifier_pipeline_vi.md b/docs/_posts/ahmedlone127/2024-09-27-vietnamese_poem_classifier_pipeline_vi.md new file mode 100644 index 00000000000000..c4ff5474749da9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-vietnamese_poem_classifier_pipeline_vi.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Vietnamese vietnamese_poem_classifier_pipeline pipeline BertForSequenceClassification from Anshler +author: John Snow Labs +name: vietnamese_poem_classifier_pipeline +date: 2024-09-27 +tags: [vi, open_source, pipeline, onnx] +task: Text Classification +language: vi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_poem_classifier_pipeline` is a Vietnamese model originally trained by Anshler. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_poem_classifier_pipeline_vi_5.5.0_3.0_1727404816824.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_poem_classifier_pipeline_vi_5.5.0_3.0_1727404816824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("vietnamese_poem_classifier_pipeline", lang = "vi") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("vietnamese_poem_classifier_pipeline", lang = "vi") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vietnamese_poem_classifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|vi| +|Size:|414.5 MB| + +## References + +https://huggingface.co/Anshler/vietnamese-poem-classifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-vietnamese_poem_classifier_vi.md b/docs/_posts/ahmedlone127/2024-09-27-vietnamese_poem_classifier_vi.md new file mode 100644 index 00000000000000..8b91233a96a9c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-vietnamese_poem_classifier_vi.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Vietnamese vietnamese_poem_classifier BertForSequenceClassification from Anshler +author: John Snow Labs +name: vietnamese_poem_classifier +date: 2024-09-27 +tags: [vi, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: vi +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vietnamese_poem_classifier` is a Vietnamese model originally trained by Anshler. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vietnamese_poem_classifier_vi_5.5.0_3.0_1727404791123.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vietnamese_poem_classifier_vi_5.5.0_3.0_1727404791123.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("vietnamese_poem_classifier","vi") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("vietnamese_poem_classifier", "vi") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vietnamese_poem_classifier| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|vi| +|Size:|414.5 MB| + +## References + +https://huggingface.co/Anshler/vietnamese-poem-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-waste_classification_en.md b/docs/_posts/ahmedlone127/2024-09-27-waste_classification_en.md new file mode 100644 index 00000000000000..14332785b947cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-waste_classification_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English waste_classification BertForSequenceClassification from XYZ123XYZ +author: John Snow Labs +name: waste_classification +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`waste_classification` is a English model originally trained by XYZ123XYZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/waste_classification_en_5.5.0_3.0_1727406170492.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/waste_classification_en_5.5.0_3.0_1727406170492.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("waste_classification","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("waste_classification", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|waste_classification| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/XYZ123XYZ/waste-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-word2affect_spanish_es.md b/docs/_posts/ahmedlone127/2024-09-27-word2affect_spanish_es.md new file mode 100644 index 00000000000000..40b6cfda555e17 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-word2affect_spanish_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish word2affect_spanish BertForSequenceClassification from hplisiecki +author: John Snow Labs +name: word2affect_spanish +date: 2024-09-27 +tags: [es, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`word2affect_spanish` is a Castilian, Spanish model originally trained by hplisiecki. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/word2affect_spanish_es_5.5.0_3.0_1727414910835.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/word2affect_spanish_es_5.5.0_3.0_1727414910835.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("word2affect_spanish","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("word2affect_spanish", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|word2affect_spanish| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.8 MB| + +## References + +https://huggingface.co/hplisiecki/word2affect_spanish \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-word2affect_spanish_pipeline_es.md b/docs/_posts/ahmedlone127/2024-09-27-word2affect_spanish_pipeline_es.md new file mode 100644 index 00000000000000..83005f26d47b51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-word2affect_spanish_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish word2affect_spanish_pipeline pipeline BertForSequenceClassification from hplisiecki +author: John Snow Labs +name: word2affect_spanish_pipeline +date: 2024-09-27 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`word2affect_spanish_pipeline` is a Castilian, Spanish model originally trained by hplisiecki. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/word2affect_spanish_pipeline_es_5.5.0_3.0_1727414932459.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/word2affect_spanish_pipeline_es_5.5.0_3.0_1727414932459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("word2affect_spanish_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("word2affect_spanish_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|word2affect_spanish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|411.8 MB| + +## References + +https://huggingface.co/hplisiecki/word2affect_spanish + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-wos46985bert_en.md b/docs/_posts/ahmedlone127/2024-09-27-wos46985bert_en.md new file mode 100644 index 00000000000000..758dcca40c0bb9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-wos46985bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English wos46985bert BertForSequenceClassification from terran-ai +author: John Snow Labs +name: wos46985bert +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`wos46985bert` is a English model originally trained by terran-ai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/wos46985bert_en_5.5.0_3.0_1727405355494.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/wos46985bert_en_5.5.0_3.0_1727405355494.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("wos46985bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("wos46985bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|wos46985bert| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.8 MB| + +## References + +https://huggingface.co/terran-ai/WOS46985Bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_100k_en.md b/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_100k_en.md new file mode 100644 index 00000000000000..753f5ede8cb36a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_100k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English yelp_polarity_tuned_bert_base_100k BertForSequenceClassification from kbang2021 +author: John Snow Labs +name: yelp_polarity_tuned_bert_base_100k +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_tuned_bert_base_100k` is a English model originally trained by kbang2021. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_polarity_tuned_bert_base_100k_en_5.5.0_3.0_1727408483608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_tuned_bert_base_100k_en_5.5.0_3.0_1727408483608.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("yelp_polarity_tuned_bert_base_100k","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("yelp_polarity_tuned_bert_base_100k", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yelp_polarity_tuned_bert_base_100k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/kbang2021/yelp_polarity_tuned_bert_base_100K \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_100k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_100k_pipeline_en.md new file mode 100644 index 00000000000000..6cfddecf906d71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_100k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English yelp_polarity_tuned_bert_base_100k_pipeline pipeline BertForSequenceClassification from kbang2021 +author: John Snow Labs +name: yelp_polarity_tuned_bert_base_100k_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_tuned_bert_base_100k_pipeline` is a English model originally trained by kbang2021. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_polarity_tuned_bert_base_100k_pipeline_en_5.5.0_3.0_1727408512209.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_tuned_bert_base_100k_pipeline_en_5.5.0_3.0_1727408512209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("yelp_polarity_tuned_bert_base_100k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("yelp_polarity_tuned_bert_base_100k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yelp_polarity_tuned_bert_base_100k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/kbang2021/yelp_polarity_tuned_bert_base_100K + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_10k_en.md b/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_10k_en.md new file mode 100644 index 00000000000000..164a93a258e4fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_10k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English yelp_polarity_tuned_bert_base_10k BertForSequenceClassification from kbang2021 +author: John Snow Labs +name: yelp_polarity_tuned_bert_base_10k +date: 2024-09-27 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_tuned_bert_base_10k` is a English model originally trained by kbang2021. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_polarity_tuned_bert_base_10k_en_5.5.0_3.0_1727412437018.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_tuned_bert_base_10k_en_5.5.0_3.0_1727412437018.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("yelp_polarity_tuned_bert_base_10k","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("yelp_polarity_tuned_bert_base_10k", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yelp_polarity_tuned_bert_base_10k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/kbang2021/yelp_polarity_tuned_bert_base_10K \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_10k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_10k_pipeline_en.md new file mode 100644 index 00000000000000..6ec64647cf5d84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-09-27-yelp_polarity_tuned_bert_base_10k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English yelp_polarity_tuned_bert_base_10k_pipeline pipeline BertForSequenceClassification from kbang2021 +author: John Snow Labs +name: yelp_polarity_tuned_bert_base_10k_pipeline +date: 2024-09-27 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yelp_polarity_tuned_bert_base_10k_pipeline` is a English model originally trained by kbang2021. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yelp_polarity_tuned_bert_base_10k_pipeline_en_5.5.0_3.0_1727412461060.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yelp_polarity_tuned_bert_base_10k_pipeline_en_5.5.0_3.0_1727412461060.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("yelp_polarity_tuned_bert_base_10k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("yelp_polarity_tuned_bert_base_10k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yelp_polarity_tuned_bert_base_10k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/kbang2021/yelp_polarity_tuned_bert_base_10K + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_iq3_m_en.md new file mode 100644 index 00000000000000..930f9a232d7d68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_iq3_m +date: 2024-10-10 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq3_m_en_5.5.0_3.0_1728575178358.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq3_m_en_5.5.0_3.0_1728575178358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_iq3_m| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_iq4_xs_en.md b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_iq4_xs_en.md new file mode 100644 index 00000000000000..f8ac691adc0dca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_iq4_xs_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_iq4_xs AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_iq4_xs +date: 2024-10-10 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_iq4_xs` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq4_xs_en_5.5.0_3.0_1728575247990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq4_xs_en_5.5.0_3.0_1728575247990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq4_xs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq4_xs", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_iq4_xs| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q3_k_l_en.md new file mode 100644 index 00000000000000..fa8462a8e0f44f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q3_k_l +date: 2024-10-10 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q3_k_l_en_5.5.0_3.0_1728575314785.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q3_k_l_en_5.5.0_3.0_1728575314785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q3_k_l| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q4_k_m_en.md new file mode 100644 index 00000000000000..6b255912c3f24a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q4_k_m +date: 2024-10-10 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q4_k_m_en_5.5.0_3.0_1728575388230.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q4_k_m_en_5.5.0_3.0_1728575388230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q4_k_m| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q5_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q5_k_m_en.md new file mode 100644 index 00000000000000..7b271fcc87c8d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q5_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q5_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q5_k_m +date: 2024-10-10 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q5_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q5_k_m_en_5.5.0_3.0_1728575468002.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q5_k_m_en_5.5.0_3.0_1728575468002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q5_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q5_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q5_k_m| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.9 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q6_k_en.md new file mode 100644 index 00000000000000..98cb76be59faaa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q6_k +date: 2024-10-10 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q6_k_en_5.5.0_3.0_1728575557458.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q6_k_en_5.5.0_3.0_1728575557458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q6_k| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|2.1 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q8_0_en.md new file mode 100644 index 00000000000000..262a5108425f10 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-gemma_2_2b_it_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q8_0 +date: 2024-10-10 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q8_0_en_5.5.0_3.0_1728575672163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q8_0_en_5.5.0_3.0_1728575672163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q8_0| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|2.7 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-llama_3.2_3b_instruct_q3_k_l_xx.md b/docs/_posts/ahmedlone127/2024-10-10-llama_3.2_3b_instruct_q3_k_l_xx.md new file mode 100644 index 00000000000000..bc26f92d85a6c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-llama_3.2_3b_instruct_q3_k_l_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_3b_instruct_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_3b_instruct_q3_k_l +date: 2024-10-10 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, tensorflow] +task: Text Generation +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_3b_instruct_q3_k_l` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q3_k_l_xx_5.5.0_3.0_1728575951058.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q3_k_l_xx_5.5.0_3.0_1728575951058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q3_k_l","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q3_k_l", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_3b_instruct_q3_k_l| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|1.8 GB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-10-llama_3.2_3b_instruct_q4_k_m_xx.md b/docs/_posts/ahmedlone127/2024-10-10-llama_3.2_3b_instruct_q4_k_m_xx.md new file mode 100644 index 00000000000000..9b069bb7a6235a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-10-llama_3.2_3b_instruct_q4_k_m_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_3b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_3b_instruct_q4_k_m +date: 2024-10-10 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, tensorflow] +task: Text Generation +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_3b_instruct_q4_k_m` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q4_k_m_xx_5.5.0_3.0_1728576043870.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q4_k_m_xx_5.5.0_3.0_1728576043870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q4_k_m","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q4_k_m", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_3b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|2.0 GB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-11-sent_roberta_base_en.md b/docs/_posts/ahmedlone127/2024-10-11-sent_roberta_base_en.md new file mode 100644 index 00000000000000..69a00468280fd3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-11-sent_roberta_base_en.md @@ -0,0 +1,77 @@ +--- +layout: model +title: RoBERTa Base Sentence Embeddings(sent_roberta_base) +author: John Snow Labs +name: sent_roberta_base +date: 2024-10-11 +tags: [sentence_embeddings, en, english, roberta, open_source, onnx, openvino] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: RoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is case-sensitive: it makes a difference between english and English. + +RoBERTa is a transformers model pretrained on a large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labeling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts. + +More precisely, it was pretrained with the Masked language modeling (MLM) objective. Taking a sentence, the model randomly masks 15% of the words in the input then runs the entire masked sentence through the model and has to predict the masked words. This is different from traditional recurrent neural networks (RNNs) that usually see the words one after the other, or from autoregressive models like GPT which internally mask the future tokens. It allows the model to learn a bidirectional representation of the sentence. + +This way, the model learns an inner representation of the English language that can then be used to extract features useful for downstream tasks: if you have a dataset of labeled sentences, for instance, you can train a standard classifier using the features produced by the BERT model as inputs. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_roberta_base_en_5.5.0_3.0_1728677006918.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_roberta_base_en_5.5.0_3.0_1728677006918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings = RoBertaSentenceEmbeddings.pretrained("sent_roberta_base", "en") \ + .setInputCols("sentence") \ + .setOutputCol("embeddings") +``` +```scala +val embeddings = RoBertaSentenceEmbeddings.pretrained("sent_roberta_base", "en") + .setInputCols("sentence") + .setOutputCol("embeddings") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_roberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[sentence_embeddings]| +|Language:|en| +|Size:|297.7 MB| +|Max sentence length:|32| + +## References + +References + +https://huggingface.co/FacebookAI/roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-11-snowflake_artic_m_en.md b/docs/_posts/ahmedlone127/2024-10-11-snowflake_artic_m_en.md new file mode 100644 index 00000000000000..ef87897d8978ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-11-snowflake_artic_m_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: SnowFlake Medium Model +author: John Snow Labs +name: snowflake_artic_m +date: 2024-10-11 +tags: [embeddings, snowflake, en, open_source, onnx, openvino] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: SnowFlakeEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained SnowFlakeEmbeddings, adataped from huggingface imported to Spark-NLP to provide scalability and production-readiness. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/snowflake_artic_m_en_5.5.0_3.0_1728683126777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/snowflake_artic_m_en_5.5.0_3.0_1728683126777.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') + +snowflake = SnowFlakeEmbeddings.pretrained("snowflake_artic_m","en") \ + .setInputCols("document") \ + .setOutputCol("embeddings") \ + +pipeline = Pipeline().setStages([documentAssembler, snowflake]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val snowflake = SnowFlakeEmbeddings.pretrained("snowflake_artic_m", "en") + .setInputCols("documents") + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, snowflake)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|snowflake_artic_m| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[snowflake]| +|Language:|en| +|Size:|405.7 MB| + +## References + +https://huggingface.co/Snowflake/snowflake-arctic-embed-m \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-13-uae_large_v1_en.md b/docs/_posts/ahmedlone127/2024-10-13-uae_large_v1_en.md new file mode 100644 index 00000000000000..8ff75bcb369cbc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-13-uae_large_v1_en.md @@ -0,0 +1,125 @@ +--- +layout: model +title: UAE-Large-V1 for Sentence Embeddings +author: John Snow Labs +name: uae_large_v1 +date: 2024-10-13 +tags: [uae, en, sentence, embeddings, open_source, onnx, openvino] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: UAEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +UAE is a novel angle-optimized text embedding model, designed to improve semantic textual +similarity tasks, which are crucial for Large Language Model (LLM) applications. By +introducing angle optimization in a complex space, AnglE effectively mitigates saturation of +the cosine similarity function. + +This model is based on UAE-Large-V1 and was orignally exported from https://huggingface.co/WhereIsAI/UAE-Large-V1. Several embedding pooling strategies can be set. Please refer to the class for more information. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/uae_large_v1_en_5.5.0_3.0_1728822609847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/uae_large_v1_en_5.5.0_3.0_1728822609847.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 +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") +embeddings = UAEEmbeddings.pretrained() \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") +embeddingsFinisher = EmbeddingsFinisher() \ + .setInputCols("embeddings") \ + .setOutputCols("finished_embeddings") \ + .setOutputAsVector(True) +pipeline = Pipeline().setStages([ + documentAssembler, + embeddings, + embeddingsFinisher +]) +data = spark.createDataFrame([["hello world", "hello moon"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.selectExpr("explode(finished_embeddings) as result").show(5, 80) +``` +```scala +import spark.implicits._ +import com.johnsnowlabs.nlp.base.DocumentAssembler +import com.johnsnowlabs.nlp.annotators.Tokenizer +import com.johnsnowlabs.nlp.embeddings.UAEEmbeddings +import com.johnsnowlabs.nlp.EmbeddingsFinisher +import org.apache.spark.ml.Pipeline +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") +val embeddings = UAEEmbeddings.pretrained() + .setInputCols("document") + .setOutputCol("UAE_embeddings") +val embeddingsFinisher = new EmbeddingsFinisher() + .setInputCols("UAE_embeddings") + .setOutputCols("finished_embeddings") + .setOutputAsVector(true) +val pipeline = new Pipeline().setStages(Array( + documentAssembler, + embeddings, + embeddingsFinisher +)) +val data = Seq("hello world", "hello moon").toDF("text") +val result = pipeline.fit(data).transform(data) +result.selectExpr("explode(finished_embeddings) as result").show(5, 80) +``` +
+ +## Results + +```bash + ++--------------------------------------------------------------------------------+ +| result| ++--------------------------------------------------------------------------------+ +|[0.50387806, 0.5861606, 0.35129607, -0.76046336, -0.32446072, -0.117674336, 0...| +|[0.6660665, 0.961762, 0.24854276, -0.1018044, -0.6569202, 0.027635604, 0.1915...| ++--------------------------------------------------------------------------------+ +``` + +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|uae_large_v1| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/WhereIsAI/UAE-Large-V1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-14-sent_xlm_roberta_base_xx.md b/docs/_posts/ahmedlone127/2024-10-14-sent_xlm_roberta_base_xx.md new file mode 100644 index 00000000000000..427d32ee52e1d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-14-sent_xlm_roberta_base_xx.md @@ -0,0 +1,80 @@ +--- +layout: model +title: XLM-RoBERTa Base Sentence Embeddings (sent_xlm_roberta_base) +author: John Snow Labs +name: sent_xlm_roberta_base +date: 2024-10-14 +tags: [multilingual, xx, sentence_embeddings, xlm_roberta, open_source, tensorflow] +task: Embeddings +language: xx +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +[XLM-RoBERTa](https://ai.facebook.com/blog/-xlm-r-state-of-the-art-cross-lingual-understanding-through-self-supervision/) is a scaled cross-lingual sentence encoder. It is trained on 2.5T of data across 100 languages data filtered from Common Crawl. XLM-R achieves state-of-the-arts results on multiple cross-lingual benchmarks. + +The XLM-RoBERTa model was proposed in [Unsupervised Cross-lingual Representation Learning at Scale](https://arxiv.org/abs/1911.02116) by Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. + +It is based on Facebook's RoBERTa model released in 2019. It is a large multi-lingual language model, trained on 2.5TB of filtered CommonCrawl data. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_xx_5.5.0_3.0_1728933428578.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_xlm_roberta_base_xx_5.5.0_3.0_1728933428578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base", "xx") \ + .setInputCols("sentence") \ + .setOutputCol("embeddings") +``` +```scala +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_xlm_roberta_base", "xx") + .setInputCols("sentence") + .setOutputCol("embeddings") +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.embed_sentence.xlm_roberta.base").predict("""Put your text here.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_xlm_roberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[sentence_embeddings]| +|Language:|xx| +|Size:|655.0 MB| +|Case sensitive:|true| +|Max sentence length:|32| + +## References + +https://huggingface.co/xlm-roberta-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-16-asr_hubert_large_ls960_en.md b/docs/_posts/ahmedlone127/2024-10-16-asr_hubert_large_ls960_en.md new file mode 100644 index 00000000000000..4100f0edb7e19f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-16-asr_hubert_large_ls960_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: ASR HubertForCTC - asr_hubert_large_ls960 +author: John Snow Labs +name: asr_hubert_large_ls960 +date: 2024-10-16 +tags: [hubert, en, open_source, onnx, openvino] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +“ +Hubert Model with a language modeling head on top for Connectionist Temporal Classification (CTC). Hubert was proposed in HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units by Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, Abdelrahman Mohamed. + +The large model fine-tuned on 960h of Librispeech on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_hubert_large_ls960_en_5.5.0_3.0_1729090392896.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_hubert_large_ls960_en_5.5.0_3.0_1729090392896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +audio_assembler = AudioAssembler()\ + .setInputCol("audio_content")\ + .setOutputCol("audio_assembler") + +speech_to_text = HubertForCTC.pretrained("asr_hubert_large_ls960", "en") .setInputCols("audio_assembler")\ + .setOutputCol("text") + +pipeline = Pipeline(stages=[ + audio_assembler, + speech_to_text, +]) + +pipelineModel = pipeline.fit(audioDf) + +pipelineDF = pipelineModel.transform(audioDf) +``` +```scala +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = HubertForCTC + .pretrained("asr_hubert_large_ls960", "en") + .setInputCols("audio_assembler") + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(audioDf) + +val pipelineDF = pipelineModel.transform(audioDf) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_hubert_large_ls960| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/facebook/hubert-large-ls960-ft \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-17-asr_wav2vec2_base_960h_en.md b/docs/_posts/ahmedlone127/2024-10-17-asr_wav2vec2_base_960h_en.md new file mode 100644 index 00000000000000..d728ea1164525c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-17-asr_wav2vec2_base_960h_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English asr_wav2vec2_base_960h TFWav2Vec2ForCTC from facebook +author: John Snow Labs +name: asr_wav2vec2_base_960h +date: 2024-10-17 +tags: [wav2vec2, en, open_source, onnx, openvino] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: Wav2Vec2ForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +“ + + + Pretrained Wav2vec2 model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.asr_wav2vec2_base_960h_by_facebook is a English model originally trained by facebook. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_wav2vec2_base_960h_en_5.5.0_3.0_1729165403118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_wav2vec2_base_960h_en_5.5.0_3.0_1729165403118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +audio_assembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speech_to_text = Wav2Vec2ForCTC \ + .pretrained("asr_wav2vec2_base_960h", "en")\ + .setInputCols("audio_assembler") \ + .setOutputCol("text") +``` +```scala +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = Wav2Vec2ForCTC + .pretrained("asr_wav2vec2_base_960h", "en") + .setInputCols("audio_assembler") + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(audioDf) + +val pipelineDF = pipelineModel.transform(audioDf) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_wav2vec2_base_960h| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|233.0 MB| + +## References + +https://huggingface.co/facebook/wav2vec2-base-960h \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-18-zero_shot_classifier_clip_vit_base_patch32_en.md b/docs/_posts/ahmedlone127/2024-10-18-zero_shot_classifier_clip_vit_base_patch32_en.md new file mode 100644 index 00000000000000..4003797b319cf4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-18-zero_shot_classifier_clip_vit_base_patch32_en.md @@ -0,0 +1,154 @@ +--- +layout: model +title: Image Zero Shot Classification with CLIP +author: John Snow Labs +name: zero_shot_classifier_clip_vit_base_patch32 +date: 2024-10-18 +tags: [classification, image, en, zero_shot, open_source, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +CLIP (Contrastive Language-Image Pre-Training) is a neural network that was trained on image +and text pairs. It has the ability to predict images without training on any hard-coded +labels. This makes it very flexible, as labels can be provided during inference. This is +similar to the zero-shot capabilities of the GPT-2 and 3 models. + +This model was imported from huggingface transformers: +https://huggingface.co/openai/clip-vit-base-patch32 + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/zero_shot_classifier_clip_vit_base_patch32_en_5.5.0_3.0_1729258523690.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/zero_shot_classifier_clip_vit_base_patch32_en_5.5.0_3.0_1729258523690.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 + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +imageAssembler: ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +imageClassifier = CLIPForZeroShotClassification \ + .pretrained() \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([imageAssembler, imageClassifier]) +pipelineDF = pipeline.fit(imageDF).transform(imageDF) +pipelineDF \ + .selectExpr("reverse(split(image.origin, '/'))[0] as image_name", "label.result") \ + .show(truncate=False) +``` +```scala +import com.johnsnowlabs.nlp.ImageAssembler +import com.johnsnowlabs.nlp.annotator._ +import org.apache.spark.ml.Pipeline +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") +val imageAssembler: ImageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") +val imageClassifier = CLIPForZeroShotClassification + .pretrained() + .setInputCols("image_assembler") + .setOutputCol("label") + .setCandidateLabels(candidateLabels) +val pipeline = + new Pipeline().setStages(Array(imageAssembler, imageClassifier)).fit(imageDF).transform(imageDF) +pipeline + .selectExpr("reverse(split(image.origin, '/'))[0] as image_name", "label.result") + .show(truncate = false) +``` +
+ +## Results + +```bash + ++-----------------+-----------------------+ +|image_name |result | ++-----------------+-----------------------+ +|palace.JPEG |[a photo of a room] | +|egyptian_cat.jpeg|[a photo of a cat] | +|hippopotamus.JPEG|[a photo of a hippo] | +|hen.JPEG |[a photo of a hen] | +|ostrich.JPEG |[a photo of an ostrich]| +|junco.JPEG |[a photo of a bird] | +|bluetick.jpg |[a photo of a dog] | +|chihuahua.jpg |[a photo of a dog] | +|tractor.JPEG |[a photo of a tractor] | +|ox.JPEG |[a photo of an ox] | ++-----------------+-----------------------+ +``` + +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|zero_shot_classifier_clip_vit_base_patch32| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[classification]| +|Language:|en| +|Size:|397.1 MB| + +## References + +https://huggingface.co/openai/clip-vit-base-patch32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-19-image_classifier_convnext_tiny_224_local_en.md b/docs/_posts/ahmedlone127/2024-10-19-image_classifier_convnext_tiny_224_local_en.md new file mode 100644 index 00000000000000..78ebe1e13fbb50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-19-image_classifier_convnext_tiny_224_local_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English image_classifier_convnext_tiny_224_local ConvNextForImageClassification +author: John Snow Labs +name: image_classifier_convnext_tiny_224_local +date: 2024-10-19 +tags: [imagenet, image_classification, en, open_source, onnx, openvino] +task: Image Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: ConvNextForImageClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained ConvNext model for Image Classification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. + +The ConvNeXT model was proposed in A ConvNet for the 2020s by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_convnext_tiny_224_local_en_5.5.0_3.0_1729378592800.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_convnext_tiny_224_local_en_5.5.0_3.0_1729378592800.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +image_assembler = ImageAssembler() .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = ConvNextForImageClassification \ + .pretrained("image_classifier_convnext_tiny_224_local", "en") .setInputCols("image_assembler") \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[ + image_assembler, + imageClassifier, +]) + +pipelineModel = pipeline.fit(imageDF) + +pipelineDF = pipelineModel.transform(imageDF) +``` +```scala +val imageAssembler = new ImageAssembler() +.setInputCol("image") +.setOutputCol("image_assembler") + +val imageClassifier = ConvNextForImageClassification +.pretrained("image_classifier_convnext_tiny_224_local", "en") +.setInputCols("image_assembler") +.setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) + +val pipelineModel = pipeline.fit(imageDF) + +val pipelineDF = pipelineModel.transform(imageDF) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|image_classifier_convnext_tiny_224_local| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[class]| +|Language:|en| +|Size:|107.4 MB| + +## References + +https://huggingface.co/facebook/convnext-tiny-224 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-19-image_classifier_swin_base_patch4_window7_224_en.md b/docs/_posts/ahmedlone127/2024-10-19-image_classifier_swin_base_patch4_window7_224_en.md new file mode 100644 index 00000000000000..597d00396afd2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-19-image_classifier_swin_base_patch4_window7_224_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English image_classifier_swin_base_patch4_window7_224 SwinForImageClassification +author: John Snow Labs +name: image_classifier_swin_base_patch4_window7_224 +date: 2024-10-19 +tags: [swin, image_classification, en, open_source, onnx, openvino] +task: Image Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: SwinForImageClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Swin model for Image Classification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. + +Swin Transformer was introduced in the paper Swin Transformer: Hierarchical Vision Transformer using Shifted Windows by Liu et al. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window7_224_en_5.5.0_3.0_1729373983113.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_swin_base_patch4_window7_224_en_5.5.0_3.0_1729373983113.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +image_assembler = ImageAssembler() .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = SwinForImageClassification \ + .pretrained("image_classifier_swin_base_patch4_window7_224", "en") .setInputCols("image_assembler") \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[ + image_assembler, + imageClassifier, +]) + +pipelineModel = pipeline.fit(imageDF) + +pipelineDF = pipelineModel.transform(imageDF) +``` +```scala +val imageAssembler = new ImageAssembler() +.setInputCol("image") +.setOutputCol("image_assembler") + +val imageClassifier = SwinForImageClassification +.pretrained("image_classifier_swin_base_patch4_window7_224", "en") +.setInputCols("image_assembler") +.setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) + +val pipelineModel = pipeline.fit(imageDF) + +val pipelineDF = pipelineModel.transform(imageDF) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|image_classifier_swin_base_patch4_window7_224| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[class]| +|Language:|en| +|Size:|211.9 MB| + +## References + +https://huggingface.co/openai/clip-vit-base-patch32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-19-image_classifier_vit_base_patch16_224_en.md b/docs/_posts/ahmedlone127/2024-10-19-image_classifier_vit_base_patch16_224_en.md new file mode 100644 index 00000000000000..56d4c039b5885a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-19-image_classifier_vit_base_patch16_224_en.md @@ -0,0 +1,91 @@ +--- +layout: model +title: English image_classifier_vit_base_patch16_224 ViTForImageClassification from google +author: John Snow Labs +name: image_classifier_vit_base_patch16_224 +date: 2024-10-19 +tags: [vit, image_classification, en, open_source, onnx, openvino] +task: Image Classification +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: ViTForImageClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained VIT model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.image_classifier_vit_base_patch16_224 is a English model originally trained by google. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_classifier_vit_base_patch16_224_en_5.5.0_3.0_1729341384692.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_classifier_vit_base_patch16_224_en_5.5.0_3.0_1729341384692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +image_assembler = ImageAssembler() .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = ViTForImageClassification \ + .pretrained("image_classifier_vit_base_patch16_224", "en") .setInputCols("image_assembler") \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[ + image_assembler, + imageClassifier, +]) + +pipelineModel = pipeline.fit(imageDF) + +pipelineDF = pipelineModel.transform(imageDF) +``` +```scala +val imageAssembler = new ImageAssembler() +.setInputCol("image") +.setOutputCol("image_assembler") + +val imageClassifier = ViTForImageClassification +.pretrained("image_classifier_vit_base_patch16_224", "en") +.setInputCols("image_assembler") +.setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) + +val pipelineModel = pipeline.fit(imageDF) + +val pipelineDF = pipelineModel.transform(imageDF) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|image_classifier_vit_base_patch16_224| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[class]| +|Language:|en| +|Size:|324.0 MB| + +## References + +https://huggingface.co/google/vit-base-patch16-224 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-20-image_captioning_vit_gpt2_en.md b/docs/_posts/ahmedlone127/2024-10-20-image_captioning_vit_gpt2_en.md new file mode 100644 index 00000000000000..1020f508d818fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-20-image_captioning_vit_gpt2_en.md @@ -0,0 +1,109 @@ +--- +layout: model +title: Image Caption with VisionEncoderDecoder ViT GPT2 +author: John Snow Labs +name: image_captioning_vit_gpt2 +date: 2024-10-20 +tags: [en, image_classification, vit, gpt2, captioning, open_source, onnx] +task: Image Captioning +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: onnx +annotator: VisionEncoderDecoderForImageCaptioning +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +This is an image captioning model using ViT to encode images and GPT2 to generate captions. Original model from https://huggingface.co/nlpconnect/vit-gpt2-image-captioning + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_captioning_vit_gpt2_en_5.5.0_3.0_1729463000155.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_captioning_vit_gpt2_en_5.5.0_3.0_1729463000155.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 +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") +imageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") +imageCaptioning = VisionEncoderDecoderForImageCaptioning \ + .pretrained() \ + .setBeamSize(2) \ + .setDoSample(False) \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("caption") +pipeline = Pipeline().setStages([imageAssembler, imageCaptioning]) +pipelineDF = pipeline.fit(imageDF).transform(imageDF) +pipelineDF \ + .selectExpr("reverse(split(image.origin, '/'))[0] as image_name", "caption.result") .show(truncate = False) +``` +```scala +import com.johnsnowlabs.nlp.annotator._ +import com.johnsnowlabs.nlp.ImageAssembler +import org.apache.spark.ml.Pipeline + +val imageDF: DataFrame = spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val imageCaptioning = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = VisionEncoderDecoderForImageCaptioning + .pretrained() + .setBeamSize(2) + .setDoSample(false) + .setInputCols("image_assembler") + .setOutputCol("caption") + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageCaptioning)) +val pipelineDF = pipeline.fit(imageDF).transform(imageDF) + +pipelineDF + .selectExpr("reverse(split(image.origin, '/'))[0] as image_name", "caption.result") + .show(truncate = false) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|image_captioning_vit_gpt2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[caption]| +|Language:|en| +|Size:|894.8 MB| + +## References + +https://huggingface.co/nlpconnect/vit-gpt2-image-captioning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-28-image_captioning_vit_gpt2_en.md b/docs/_posts/ahmedlone127/2024-10-28-image_captioning_vit_gpt2_en.md new file mode 100644 index 00000000000000..b7907d4c386d66 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-28-image_captioning_vit_gpt2_en.md @@ -0,0 +1,109 @@ +--- +layout: model +title: Image Caption with VisionEncoderDecoder ViT GPT2 +author: John Snow Labs +name: image_captioning_vit_gpt2 +date: 2024-10-28 +tags: [en, image_classification, vit, gpt2, captioning, open_source, openvino] +task: Image Captioning +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: VisionEncoderDecoderForImageCaptioning +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +This is an image captioning model using ViT to encode images and GPT2 to generate captions. Original model from https://huggingface.co/nlpconnect/vit-gpt2-image-captioning + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/image_captioning_vit_gpt2_en_5.5.0_3.0_1730123370533.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/image_captioning_vit_gpt2_en_5.5.0_3.0_1730123370533.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 +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") +imageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") +imageCaptioning = VisionEncoderDecoderForImageCaptioning \ + .pretrained() \ + .setBeamSize(2) \ + .setDoSample(False) \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("caption") +pipeline = Pipeline().setStages([imageAssembler, imageCaptioning]) +pipelineDF = pipeline.fit(imageDF).transform(imageDF) +pipelineDF \ + .selectExpr("reverse(split(image.origin, '/'))[0] as image_name", "caption.result") .show(truncate = False) +``` +```scala +import com.johnsnowlabs.nlp.annotator._ +import com.johnsnowlabs.nlp.ImageAssembler +import org.apache.spark.ml.Pipeline + +val imageDF: DataFrame = spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val imageCaptioning = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = VisionEncoderDecoderForImageCaptioning + .pretrained() + .setBeamSize(2) + .setDoSample(false) + .setInputCols("image_assembler") + .setOutputCol("caption") + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageCaptioning)) +val pipelineDF = pipeline.fit(imageDF).transform(imageDF) + +pipelineDF + .selectExpr("reverse(split(image.origin, '/'))[0] as image_name", "caption.result") + .show(truncate = false) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|image_captioning_vit_gpt2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[caption]| +|Language:|en| +|Size:|894.6 MB| + +## References + +https://huggingface.co/nlpconnect/vit-gpt2-image-captioning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_iq3_m_en.md new file mode 100644 index 00000000000000..800cd5c2da0dd3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_iq3_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq3_m_en_5.5.1_3.0_1730198545090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq3_m_en_5.5.1_3.0_1730198545090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_iq4_xs_en.md b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_iq4_xs_en.md new file mode 100644 index 00000000000000..ee8effed849a5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_iq4_xs_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_iq4_xs AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_iq4_xs +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_iq4_xs` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq4_xs_en_5.5.1_3.0_1730198610792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_iq4_xs_en_5.5.1_3.0_1730198610792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq4_xs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_iq4_xs", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_iq4_xs| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q3_k_l_en.md new file mode 100644 index 00000000000000..3f0d1bf65f9ba9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q3_k_l +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q3_k_l_en_5.5.1_3.0_1730198674631.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q3_k_l_en_5.5.1_3.0_1730198674631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q4_k_m_en.md new file mode 100644 index 00000000000000..9465a36e6b54bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q4_k_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, tensorflow] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q4_k_m_en_5.5.1_3.0_1730198748456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q4_k_m_en_5.5.1_3.0_1730198748456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q5_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q5_k_m_en.md new file mode 100644 index 00000000000000..a9f4a599205a29 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q5_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q5_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q5_k_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q5_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q5_k_m_en_5.5.1_3.0_1730229529211.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q5_k_m_en_5.5.1_3.0_1730229529211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q5_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q5_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q5_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.9 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q6_k_en.md new file mode 100644 index 00000000000000..cb30905c2f83d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q6_k +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q6_k_en_5.5.1_3.0_1730229619613.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q6_k_en_5.5.1_3.0_1730229619613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|2.1 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q8_0_en.md new file mode 100644 index 00000000000000..09255cbff175a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-gemma_2_2b_it_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English gemma_2_2b_it_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: gemma_2_2b_it_q8_0 +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gemma_2_2b_it_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q8_0_en_5.5.1_3.0_1730229741349.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gemma_2_2b_it_q8_0_en_5.5.1_3.0_1730229741349.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("gemma_2_2b_it_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gemma_2_2b_it_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|2.7 GB| + +## References + +https://huggingface.co/lmstudio-community/gemma-2-2b-it-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q3_k_l_xx.md b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q3_k_l_xx.md new file mode 100644 index 00000000000000..2ba3187cf54129 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q3_k_l_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_1b_instruct_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_1b_instruct_q3_k_l +date: 2024-10-29 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, llamacpp] +task: Text Generation +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_1b_instruct_q3_k_l` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_1b_instruct_q3_k_l_xx_5.5.1_3.0_1730231028736.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_1b_instruct_q3_k_l_xx_5.5.1_3.0_1730231028736.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_1b_instruct_q3_k_l","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_1b_instruct_q3_k_l", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_1b_instruct_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|728.0 MB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-1B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q4_k_m_xx.md b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q4_k_m_xx.md new file mode 100644 index 00000000000000..e99e759a6bd650 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q4_k_m_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_1b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_1b_instruct_q4_k_m +date: 2024-10-29 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, llamacpp] +task: Text Generation +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_1b_instruct_q4_k_m` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_1b_instruct_q4_k_m_xx_5.5.1_3.0_1730231067664.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_1b_instruct_q4_k_m_xx_5.5.1_3.0_1730231067664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_1b_instruct_q4_k_m","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_1b_instruct_q4_k_m", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_1b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|793.2 MB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-1B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q6_k_xx.md b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q6_k_xx.md new file mode 100644 index 00000000000000..3b5030e358224d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q6_k_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_1b_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_1b_instruct_q6_k +date: 2024-10-29 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, llamacpp] +task: Text Generation +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_1b_instruct_q6_k` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_1b_instruct_q6_k_xx_5.5.1_3.0_1730231113608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_1b_instruct_q6_k_xx_5.5.1_3.0_1730231113608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_1b_instruct_q6_k","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_1b_instruct_q6_k", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_1b_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|1.0 GB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-1B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q8_0_xx.md b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q8_0_xx.md new file mode 100644 index 00000000000000..279a499da47c87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_1b_instruct_q8_0_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_1b_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_1b_instruct_q8_0 +date: 2024-10-29 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, llamacpp] +task: Text Generation +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_1b_instruct_q8_0` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_1b_instruct_q8_0_xx_5.5.1_3.0_1730231173687.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_1b_instruct_q8_0_xx_5.5.1_3.0_1730231173687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_1b_instruct_q8_0","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_1b_instruct_q8_0", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_1b_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-1B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q3_k_l_xx.md b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q3_k_l_xx.md new file mode 100644 index 00000000000000..54e5aa6b61c938 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q3_k_l_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_3b_instruct_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_3b_instruct_q3_k_l +date: 2024-10-29 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, tensorflow] +task: Text Generation +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_3b_instruct_q3_k_l` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q3_k_l_xx_5.5.1_3.0_1730199983558.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q3_k_l_xx_5.5.1_3.0_1730199983558.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q3_k_l","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q3_k_l", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_3b_instruct_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|1.8 GB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q4_k_m_xx.md b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q4_k_m_xx.md new file mode 100644 index 00000000000000..748d054a04425f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q4_k_m_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_3b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_3b_instruct_q4_k_m +date: 2024-10-29 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, tensorflow] +task: Text Generation +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_3b_instruct_q4_k_m` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q4_k_m_xx_5.5.1_3.0_1730200073838.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q4_k_m_xx_5.5.1_3.0_1730200073838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q4_k_m","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q4_k_m", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_3b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|2.0 GB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q6_k_xx.md b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q6_k_xx.md new file mode 100644 index 00000000000000..24b4cfc31890cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q6_k_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_3b_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_3b_instruct_q6_k +date: 2024-10-29 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, tensorflow] +task: Text Generation +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_3b_instruct_q6_k` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q6_k_xx_5.5.1_3.0_1730200181182.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q6_k_xx_5.5.1_3.0_1730200181182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q6_k","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q6_k", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_3b_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|2.6 GB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q8_0_xx.md b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q8_0_xx.md new file mode 100644 index 00000000000000..ed0d66be5211b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-llama_3.2_3b_instruct_q8_0_xx.md @@ -0,0 +1,101 @@ +--- +layout: model +title: Multilingual llama_3.2_3b_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: llama_3.2_3b_instruct_q8_0 +date: 2024-10-29 +tags: [xx, open_source, onnx, conversational, text_generation, text_to_text, en, de, fr, it, pt, hi, es, th, tensorflow] +task: Text Generation +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`llama_3.2_3b_instruct_q8_0` is a Multilingual model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q8_0_xx_5.5.1_3.0_1730200322185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/llama_3.2_3b_instruct_q8_0_xx_5.5.1_3.0_1730200322185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q8_0","xx") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("llama_3.2_3b_instruct_q8_0", "xx") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|llama_3.2_3b_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|xx| +|Size:|3.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Llama-3.2-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-mathstral_7b_v0.1_iq4_xs_en.md b/docs/_posts/ahmedlone127/2024-10-29-mathstral_7b_v0.1_iq4_xs_en.md new file mode 100644 index 00000000000000..dec6688b049012 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-mathstral_7b_v0.1_iq4_xs_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English mathstral_7b_v0.1_iq4_xs AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: mathstral_7b_v0.1_iq4_xs +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mathstral_7b_v0.1_iq4_xs` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mathstral_7b_v0.1_iq4_xs_en_5.5.1_3.0_1730237800768.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mathstral_7b_v0.1_iq4_xs_en_5.5.1_3.0_1730237800768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("mathstral_7b_v0.1_iq4_xs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("mathstral_7b_v0.1_iq4_xs", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mathstral_7b_v0.1_iq4_xs| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.9 GB| + +## References + +https://huggingface.co/lmstudio-community/mathstral-7B-v0.1-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-mathstral_7b_v0.1_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-29-mathstral_7b_v0.1_q3_k_l_en.md new file mode 100644 index 00000000000000..890222b79ac778 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-mathstral_7b_v0.1_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English mathstral_7b_v0.1_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: mathstral_7b_v0.1_q3_k_l +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mathstral_7b_v0.1_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mathstral_7b_v0.1_q3_k_l_en_5.5.1_3.0_1730237954284.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mathstral_7b_v0.1_q3_k_l_en_5.5.1_3.0_1730237954284.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("mathstral_7b_v0.1_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("mathstral_7b_v0.1_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mathstral_7b_v0.1_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.8 GB| + +## References + +https://huggingface.co/lmstudio-community/mathstral-7B-v0.1-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-meta_llama_3_8b_instruct_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-meta_llama_3_8b_instruct_iq3_m_en.md new file mode 100644 index 00000000000000..5390bf562028d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-meta_llama_3_8b_instruct_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English meta_llama_3_8b_instruct_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: meta_llama_3_8b_instruct_iq3_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meta_llama_3_8b_instruct_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meta_llama_3_8b_instruct_iq3_m_en_5.5.1_3.0_1730232269372.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meta_llama_3_8b_instruct_iq3_m_en_5.5.1_3.0_1730232269372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("meta_llama_3_8b_instruct_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("meta_llama_3_8b_instruct_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|meta_llama_3_8b_instruct_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.8 GB| + +## References + +https://huggingface.co/lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-mistral_7b_instruct_v0.3_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-mistral_7b_instruct_v0.3_iq3_m_en.md new file mode 100644 index 00000000000000..4554390b62da18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-mistral_7b_instruct_v0.3_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English mistral_7b_instruct_v0.3_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: mistral_7b_instruct_v0.3_iq3_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mistral_7b_instruct_v0.3_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mistral_7b_instruct_v0.3_iq3_m_en_5.5.1_3.0_1730231778040.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mistral_7b_instruct_v0.3_iq3_m_en_5.5.1_3.0_1730231778040.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("mistral_7b_instruct_v0.3_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("mistral_7b_instruct_v0.3_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mistral_7b_instruct_v0.3_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Mistral-7B-Instruct-v0.3-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-mistral_7b_instruct_v0.3_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-29-mistral_7b_instruct_v0.3_q3_k_l_en.md new file mode 100644 index 00000000000000..a9759f5aaca385 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-mistral_7b_instruct_v0.3_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English mistral_7b_instruct_v0.3_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: mistral_7b_instruct_v0.3_q3_k_l +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mistral_7b_instruct_v0.3_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mistral_7b_instruct_v0.3_q3_k_l_en_5.5.1_3.0_1730231916921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mistral_7b_instruct_v0.3_q3_k_l_en_5.5.1_3.0_1730231916921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("mistral_7b_instruct_v0.3_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("mistral_7b_instruct_v0.3_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mistral_7b_instruct_v0.3_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.8 GB| + +## References + +https://huggingface.co/lmstudio-community/Mistral-7B-Instruct-v0.3-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-phi_3.1_mini_4k_instruct_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-phi_3.1_mini_4k_instruct_iq3_m_en.md new file mode 100644 index 00000000000000..ca28f2acfd1ae4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-phi_3.1_mini_4k_instruct_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English phi_3.1_mini_4k_instruct_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: phi_3.1_mini_4k_instruct_iq3_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`phi_3.1_mini_4k_instruct_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/phi_3.1_mini_4k_instruct_iq3_m_en_5.5.1_3.0_1730235527993.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/phi_3.1_mini_4k_instruct_iq3_m_en_5.5.1_3.0_1730235527993.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("phi_3.1_mini_4k_instruct_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("phi_3.1_mini_4k_instruct_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|phi_3.1_mini_4k_instruct_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.8 GB| + +## References + +https://huggingface.co/lmstudio-community/Phi-3.1-mini-4k-instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_f32_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_f32_en.md new file mode 100644 index 00000000000000..36301b9a52ac78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_f32_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_500m_instruct_f32 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_500m_instruct_f32 +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_500m_instruct_f32` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_f32_en_5.5.1_3.0_1730243787866.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_f32_en_5.5.1_3.0_1730243787866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_f32","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_f32", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_500m_instruct_f32| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|930.2 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-500M-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_iq4_xs_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_iq4_xs_en.md new file mode 100644 index 00000000000000..c8187e025e94a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_iq4_xs_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_500m_instruct_iq4_xs AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_500m_instruct_iq4_xs +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_500m_instruct_iq4_xs` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_iq4_xs_en_5.5.1_3.0_1730243384741.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_iq4_xs_en_5.5.1_3.0_1730243384741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_iq4_xs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_iq4_xs", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_500m_instruct_iq4_xs| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|336.2 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-500M-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q4_k_m_en.md new file mode 100644 index 00000000000000..7d4471cbeacda0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_500m_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_500m_instruct_q4_k_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_500m_instruct_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_q4_k_m_en_5.5.1_3.0_1730243404853.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_q4_k_m_en_5.5.1_3.0_1730243404853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_500m_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|387.3 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-500M-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q5_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q5_k_m_en.md new file mode 100644 index 00000000000000..26a7c03e3611ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q5_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_500m_instruct_q5_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_500m_instruct_q5_k_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_500m_instruct_q5_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_q5_k_m_en_5.5.1_3.0_1730243426822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_q5_k_m_en_5.5.1_3.0_1730243426822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_q5_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_q5_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_500m_instruct_q5_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-500M-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q6_k_en.md new file mode 100644 index 00000000000000..2c90b235c1c066 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_500m_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_500m_instruct_q6_k +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_500m_instruct_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_q6_k_en_5.5.1_3.0_1730243451242.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_q6_k_en_5.5.1_3.0_1730243451242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_500m_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|485.6 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-500M-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q8_0_en.md new file mode 100644 index 00000000000000..0ff73dbf5a6768 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_500m_instruct_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_500m_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_500m_instruct_q8_0 +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_500m_instruct_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_q8_0_en_5.5.1_3.0_1730243477404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_500m_instruct_q8_0_en_5.5.1_3.0_1730243477404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_500m_instruct_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_500m_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|506.7 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-500M-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_iq4_xs_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_iq4_xs_en.md new file mode 100644 index 00000000000000..aa11aacfae37c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_iq4_xs_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_math_1.5b_instruct_iq4_xs AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_math_1.5b_instruct_iq4_xs +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_math_1.5b_instruct_iq4_xs` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_iq4_xs_en_5.5.1_3.0_1730238713389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_iq4_xs_en_5.5.1_3.0_1730238713389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_iq4_xs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_iq4_xs", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_math_1.5b_instruct_iq4_xs| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|878.6 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q4_k_m_en.md new file mode 100644 index 00000000000000..2215e50049b7d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_math_1.5b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_math_1.5b_instruct_q4_k_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_math_1.5b_instruct_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_q4_k_m_en_5.5.1_3.0_1730238760156.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_q4_k_m_en_5.5.1_3.0_1730238760156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_math_1.5b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|965.9 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q5_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q5_k_m_en.md new file mode 100644 index 00000000000000..1fd3f774ec2b4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q5_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_math_1.5b_instruct_q5_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_math_1.5b_instruct_q5_k_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_math_1.5b_instruct_q5_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_q5_k_m_en_5.5.1_3.0_1730238815393.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_q5_k_m_en_5.5.1_3.0_1730238815393.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_q5_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_q5_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_math_1.5b_instruct_q5_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q6_k_en.md new file mode 100644 index 00000000000000..761748f9ea3286 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_math_1.5b_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_math_1.5b_instruct_q6_k +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_math_1.5b_instruct_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_q6_k_en_5.5.1_3.0_1730238877334.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_q6_k_en_5.5.1_3.0_1730238877334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_math_1.5b_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q8_0_en.md new file mode 100644 index 00000000000000..198d7dc7f2d40d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-qwen2_math_1.5b_instruct_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2_math_1.5b_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2_math_1.5b_instruct_q8_0 +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2_math_1.5b_instruct_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_q8_0_en_5.5.1_3.0_1730238954990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2_math_1.5b_instruct_q8_0_en_5.5.1_3.0_1730238954990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2_math_1.5b_instruct_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2_math_1.5b_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q4_0_4_4_en.md b/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q4_0_4_4_en.md new file mode 100644 index 00000000000000..ef7fd42faf4334 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q4_0_4_4_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_coder_1.5b_chat_q4_0_4_4 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_coder_1.5b_chat_q4_0_4_4 +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_coder_1.5b_chat_q4_0_4_4` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_chat_q4_0_4_4_en_5.5.1_3.0_1730239385570.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_chat_q4_0_4_4_en_5.5.1_3.0_1730239385570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_chat_q4_0_4_4","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_chat_q4_0_4_4", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_coder_1.5b_chat_q4_0_4_4| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|824.5 MB| + +## References + +https://huggingface.co/lmstudio-community/Yi-Coder-1.5B-Chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q4_k_m_en.md new file mode 100644 index 00000000000000..8ab447212f5c0a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_coder_1.5b_chat_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_coder_1.5b_chat_q4_k_m +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_coder_1.5b_chat_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_chat_q4_k_m_en_5.5.1_3.0_1730239445307.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_chat_q4_k_m_en_5.5.1_3.0_1730239445307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_chat_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_chat_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_coder_1.5b_chat_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|944.8 MB| + +## References + +https://huggingface.co/lmstudio-community/Yi-Coder-1.5B-Chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q6_k_en.md new file mode 100644 index 00000000000000..419ec9cdc45f2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_coder_1.5b_chat_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_coder_1.5b_chat_q6_k +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_coder_1.5b_chat_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_chat_q6_k_en_5.5.1_3.0_1730239509643.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_chat_q6_k_en_5.5.1_3.0_1730239509643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_chat_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_chat_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_coder_1.5b_chat_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Yi-Coder-1.5B-Chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q8_0_en.md new file mode 100644 index 00000000000000..2669a67c077275 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-29-yi_coder_1.5b_chat_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_coder_1.5b_chat_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_coder_1.5b_chat_q8_0 +date: 2024-10-29 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_coder_1.5b_chat_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_chat_q8_0_en_5.5.1_3.0_1730239602151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_chat_q8_0_en_5.5.1_3.0_1730239602151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_chat_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_chat_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_coder_1.5b_chat_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/lmstudio-community/Yi-Coder-1.5B-Chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-alchemistcoder_ds_6.7b_iq4_xs_en.md b/docs/_posts/ahmedlone127/2024-10-30-alchemistcoder_ds_6.7b_iq4_xs_en.md new file mode 100644 index 00000000000000..359bbc77ae8266 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-alchemistcoder_ds_6.7b_iq4_xs_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English alchemistcoder_ds_6.7b_iq4_xs AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: alchemistcoder_ds_6.7b_iq4_xs +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alchemistcoder_ds_6.7b_iq4_xs` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alchemistcoder_ds_6.7b_iq4_xs_en_5.5.1_3.0_1730265657929.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alchemistcoder_ds_6.7b_iq4_xs_en_5.5.1_3.0_1730265657929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("alchemistcoder_ds_6.7b_iq4_xs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("alchemistcoder_ds_6.7b_iq4_xs", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alchemistcoder_ds_6.7b_iq4_xs| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.6 GB| + +## References + +https://huggingface.co/lmstudio-community/AlchemistCoder-DS-6.7B-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-alchemistcoder_l_7b_iq4_xs_en.md b/docs/_posts/ahmedlone127/2024-10-30-alchemistcoder_l_7b_iq4_xs_en.md new file mode 100644 index 00000000000000..09e05f27f203e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-alchemistcoder_l_7b_iq4_xs_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English alchemistcoder_l_7b_iq4_xs AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: alchemistcoder_l_7b_iq4_xs +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alchemistcoder_l_7b_iq4_xs` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alchemistcoder_l_7b_iq4_xs_en_5.5.1_3.0_1730263239155.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alchemistcoder_l_7b_iq4_xs_en_5.5.1_3.0_1730263239155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("alchemistcoder_l_7b_iq4_xs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("alchemistcoder_l_7b_iq4_xs", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alchemistcoder_l_7b_iq4_xs| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.6 GB| + +## References + +https://huggingface.co/lmstudio-community/AlchemistCoder-L-7B-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-codellama_7b_kstack_clean_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-codellama_7b_kstack_clean_iq3_m_en.md new file mode 100644 index 00000000000000..c92ec14d37dced --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-codellama_7b_kstack_clean_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English codellama_7b_kstack_clean_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: codellama_7b_kstack_clean_iq3_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codellama_7b_kstack_clean_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codellama_7b_kstack_clean_iq3_m_en_5.5.1_3.0_1730260332734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codellama_7b_kstack_clean_iq3_m_en_5.5.1_3.0_1730260332734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("codellama_7b_kstack_clean_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("codellama_7b_kstack_clean_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codellama_7b_kstack_clean_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.1 GB| + +## References + +https://huggingface.co/lmstudio-community/CodeLlama-7B-KStack-clean-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-codellama_7b_kstack_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-codellama_7b_kstack_iq3_m_en.md new file mode 100644 index 00000000000000..f002328ee30761 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-codellama_7b_kstack_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English codellama_7b_kstack_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: codellama_7b_kstack_iq3_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codellama_7b_kstack_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codellama_7b_kstack_iq3_m_en_5.5.1_3.0_1730249651434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codellama_7b_kstack_iq3_m_en_5.5.1_3.0_1730249651434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("codellama_7b_kstack_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("codellama_7b_kstack_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codellama_7b_kstack_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.1 GB| + +## References + +https://huggingface.co/lmstudio-community/CodeLlama-7B-KStack-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_iq3_m_en.md new file mode 100644 index 00000000000000..a91521acc335da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English deepseek_coder_1.3b_kexer_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: deepseek_coder_1.3b_kexer_iq3_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepseek_coder_1.3b_kexer_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepseek_coder_1.3b_kexer_iq3_m_en_5.5.1_3.0_1730266269461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepseek_coder_1.3b_kexer_iq3_m_en_5.5.1_3.0_1730266269461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_1.3b_kexer_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_1.3b_kexer_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepseek_coder_1.3b_kexer_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|667.7 MB| + +## References + +https://huggingface.co/lmstudio-community/deepseek-coder-1.3B-kexer-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q4_k_m_en.md new file mode 100644 index 00000000000000..f491a2243fa0fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English deepseek_coder_1.3b_kexer_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: deepseek_coder_1.3b_kexer_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepseek_coder_1.3b_kexer_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepseek_coder_1.3b_kexer_q4_k_m_en_5.5.1_3.0_1730266308804.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepseek_coder_1.3b_kexer_q4_k_m_en_5.5.1_3.0_1730266308804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_1.3b_kexer_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_1.3b_kexer_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepseek_coder_1.3b_kexer_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|856.9 MB| + +## References + +https://huggingface.co/lmstudio-community/deepseek-coder-1.3B-kexer-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q6_k_en.md new file mode 100644 index 00000000000000..91e7d7a526baed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English deepseek_coder_1.3b_kexer_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: deepseek_coder_1.3b_kexer_q6_k +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepseek_coder_1.3b_kexer_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepseek_coder_1.3b_kexer_q6_k_en_5.5.1_3.0_1730266358715.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepseek_coder_1.3b_kexer_q6_k_en_5.5.1_3.0_1730266358715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_1.3b_kexer_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_1.3b_kexer_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepseek_coder_1.3b_kexer_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/lmstudio-community/deepseek-coder-1.3B-kexer-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q8_0_en.md new file mode 100644 index 00000000000000..a76734385bfad2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_1.3b_kexer_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English deepseek_coder_1.3b_kexer_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: deepseek_coder_1.3b_kexer_q8_0 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepseek_coder_1.3b_kexer_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepseek_coder_1.3b_kexer_q8_0_en_5.5.1_3.0_1730266423672.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepseek_coder_1.3b_kexer_q8_0_en_5.5.1_3.0_1730266423672.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_1.3b_kexer_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_1.3b_kexer_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepseek_coder_1.3b_kexer_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/lmstudio-community/deepseek-coder-1.3B-kexer-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_6.7b_kexer_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_6.7b_kexer_iq3_m_en.md new file mode 100644 index 00000000000000..47f57a9498d13d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-deepseek_coder_6.7b_kexer_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English deepseek_coder_6.7b_kexer_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: deepseek_coder_6.7b_kexer_iq3_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deepseek_coder_6.7b_kexer_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deepseek_coder_6.7b_kexer_iq3_m_en_5.5.1_3.0_1730260963287.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deepseek_coder_6.7b_kexer_iq3_m_en_5.5.1_3.0_1730260963287.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_6.7b_kexer_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("deepseek_coder_6.7b_kexer_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deepseek_coder_6.7b_kexer_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.1 GB| + +## References + +https://huggingface.co/lmstudio-community/deepseek-coder-6.7B-kexer-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_iq4_xs_en.md b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_iq4_xs_en.md new file mode 100644 index 00000000000000..db2548cc3df05d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_iq4_xs_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English internlm2_5_1_8b_chat_iq4_xs AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: internlm2_5_1_8b_chat_iq4_xs +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`internlm2_5_1_8b_chat_iq4_xs` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_iq4_xs_en_5.5.1_3.0_1730267346885.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_iq4_xs_en_5.5.1_3.0_1730267346885.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_iq4_xs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_iq4_xs", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|internlm2_5_1_8b_chat_iq4_xs| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/lmstudio-community/internlm2_5-1_8b-chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q3_k_l_en.md new file mode 100644 index 00000000000000..346965617257f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English internlm2_5_1_8b_chat_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: internlm2_5_1_8b_chat_q3_k_l +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`internlm2_5_1_8b_chat_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q3_k_l_en_5.5.1_3.0_1730267392831.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q3_k_l_en_5.5.1_3.0_1730267392831.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|internlm2_5_1_8b_chat_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.0 GB| + +## References + +https://huggingface.co/lmstudio-community/internlm2_5-1_8b-chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q4_k_m_en.md new file mode 100644 index 00000000000000..d85e1b8d8b0e03 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English internlm2_5_1_8b_chat_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: internlm2_5_1_8b_chat_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`internlm2_5_1_8b_chat_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q4_k_m_en_5.5.1_3.0_1730267445239.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q4_k_m_en_5.5.1_3.0_1730267445239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|internlm2_5_1_8b_chat_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/lmstudio-community/internlm2_5-1_8b-chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q5_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q5_k_m_en.md new file mode 100644 index 00000000000000..8db3fc3c8ee0fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q5_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English internlm2_5_1_8b_chat_q5_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: internlm2_5_1_8b_chat_q5_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`internlm2_5_1_8b_chat_q5_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q5_k_m_en_5.5.1_3.0_1730267500355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q5_k_m_en_5.5.1_3.0_1730267500355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q5_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q5_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|internlm2_5_1_8b_chat_q5_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/lmstudio-community/internlm2_5-1_8b-chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q6_k_en.md new file mode 100644 index 00000000000000..db10871f20aab8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English internlm2_5_1_8b_chat_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: internlm2_5_1_8b_chat_q6_k +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`internlm2_5_1_8b_chat_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q6_k_en_5.5.1_3.0_1730267567662.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q6_k_en_5.5.1_3.0_1730267567662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|internlm2_5_1_8b_chat_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/lmstudio-community/internlm2_5-1_8b-chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q8_0_en.md new file mode 100644 index 00000000000000..75f74d844423a0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-internlm2_5_1_8b_chat_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English internlm2_5_1_8b_chat_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: internlm2_5_1_8b_chat_q8_0 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`internlm2_5_1_8b_chat_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q8_0_en_5.5.1_3.0_1730267652584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/internlm2_5_1_8b_chat_q8_0_en_5.5.1_3.0_1730267652584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("internlm2_5_1_8b_chat_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|internlm2_5_1_8b_chat_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.9 GB| + +## References + +https://huggingface.co/lmstudio-community/internlm2_5-1_8b-chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-meta_llama_3_8b_instruct_iq3_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-meta_llama_3_8b_instruct_iq3_m_en.md new file mode 100644 index 00000000000000..ec0ba55dbd9e6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-meta_llama_3_8b_instruct_iq3_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English meta_llama_3_8b_instruct_iq3_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: meta_llama_3_8b_instruct_iq3_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`meta_llama_3_8b_instruct_iq3_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/meta_llama_3_8b_instruct_iq3_m_en_5.5.1_3.0_1730250028909.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/meta_llama_3_8b_instruct_iq3_m_en_5.5.1_3.0_1730250028909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("meta_llama_3_8b_instruct_iq3_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("meta_llama_3_8b_instruct_iq3_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|meta_llama_3_8b_instruct_iq3_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.8 GB| + +## References + +https://huggingface.co/lmstudio-community/Meta-Llama-3-8B-Instruct-BPE-fix-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q3_k_l_en.md new file mode 100644 index 00000000000000..493bc93dd70b33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_0.5b_instruct_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_0.5b_instruct_q3_k_l +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_0.5b_instruct_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_0.5b_instruct_q3_k_l_en_5.5.1_3.0_1730250340968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_0.5b_instruct_q3_k_l_en_5.5.1_3.0_1730250340968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_0.5b_instruct_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_0.5b_instruct_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_0.5b_instruct_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|356.9 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-0.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q4_k_m_en.md new file mode 100644 index 00000000000000..37f07769b2f885 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_0.5b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_0.5b_instruct_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_0.5b_instruct_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_0.5b_instruct_q4_k_m_en_5.5.1_3.0_1730250361508.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_0.5b_instruct_q4_k_m_en_5.5.1_3.0_1730250361508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_0.5b_instruct_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_0.5b_instruct_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_0.5b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|386.9 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-0.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q6_k_en.md new file mode 100644 index 00000000000000..bfd358fd78628c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_0.5b_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_0.5b_instruct_q6_k +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_0.5b_instruct_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_0.5b_instruct_q6_k_en_5.5.1_3.0_1730250386292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_0.5b_instruct_q6_k_en_5.5.1_3.0_1730250386292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_0.5b_instruct_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_0.5b_instruct_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_0.5b_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|485.3 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-0.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q8_0_en.md new file mode 100644 index 00000000000000..9518aeecb7dc76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_0.5b_instruct_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_0.5b_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_0.5b_instruct_q8_0 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_0.5b_instruct_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_0.5b_instruct_q8_0_en_5.5.1_3.0_1730250413397.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_0.5b_instruct_q8_0_en_5.5.1_3.0_1730250413397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_0.5b_instruct_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_0.5b_instruct_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_0.5b_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|506.3 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-0.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q3_k_l_en.md new file mode 100644 index 00000000000000..18fff1b077430a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_1.5b_instruct_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_1.5b_instruct_q3_k_l +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_1.5b_instruct_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_1.5b_instruct_q3_k_l_en_5.5.1_3.0_1730251052001.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_1.5b_instruct_q3_k_l_en_5.5.1_3.0_1730251052001.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_1.5b_instruct_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_1.5b_instruct_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_1.5b_instruct_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|874.6 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q4_k_m_en.md new file mode 100644 index 00000000000000..aebd366b1df9da --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_1.5b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_1.5b_instruct_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_1.5b_instruct_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_1.5b_instruct_q4_k_m_en_5.5.1_3.0_1730251099082.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_1.5b_instruct_q4_k_m_en_5.5.1_3.0_1730251099082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_1.5b_instruct_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_1.5b_instruct_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_1.5b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|966.5 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q6_k_en.md new file mode 100644 index 00000000000000..25811827254a12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_1.5b_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_1.5b_instruct_q6_k +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_1.5b_instruct_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_1.5b_instruct_q6_k_en_5.5.1_3.0_1730251153966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_1.5b_instruct_q6_k_en_5.5.1_3.0_1730251153966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_1.5b_instruct_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_1.5b_instruct_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_1.5b_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q8_0_en.md new file mode 100644 index 00000000000000..e2fef4ba8e2bc0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_1.5b_instruct_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_1.5b_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_1.5b_instruct_q8_0 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_1.5b_instruct_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_1.5b_instruct_q8_0_en_5.5.1_3.0_1730251224464.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_1.5b_instruct_q8_0_en_5.5.1_3.0_1730251224464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_1.5b_instruct_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_1.5b_instruct_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_1.5b_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q3_k_l_en.md new file mode 100644 index 00000000000000..56ab7ad7f483e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_3b_instruct_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_3b_instruct_q3_k_l +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_3b_instruct_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_3b_instruct_q3_k_l_en_5.5.1_3.0_1730247550382.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_3b_instruct_q3_k_l_en_5.5.1_3.0_1730247550382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_3b_instruct_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_3b_instruct_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_3b_instruct_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q4_k_m_en.md new file mode 100644 index 00000000000000..00bbdded3a2cd2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_3b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_3b_instruct_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_3b_instruct_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_3b_instruct_q4_k_m_en_5.5.1_3.0_1730247635762.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_3b_instruct_q4_k_m_en_5.5.1_3.0_1730247635762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_3b_instruct_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_3b_instruct_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_3b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.9 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q6_k_en.md new file mode 100644 index 00000000000000..153394b01b8fc0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_3b_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_3b_instruct_q6_k +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_3b_instruct_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_3b_instruct_q6_k_en_5.5.1_3.0_1730247736241.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_3b_instruct_q6_k_en_5.5.1_3.0_1730247736241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_3b_instruct_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_3b_instruct_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_3b_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|2.5 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q8_0_en.md new file mode 100644 index 00000000000000..c3d121bfc28e47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_3b_instruct_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_3b_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_3b_instruct_q8_0 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_3b_instruct_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_3b_instruct_q8_0_en_5.5.1_3.0_1730247872137.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_3b_instruct_q8_0_en_5.5.1_3.0_1730247872137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_3b_instruct_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_3b_instruct_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_3b_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.1 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-3B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q3_k_l_en.md new file mode 100644 index 00000000000000..c8703765f7ecf9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_coder_1.5b_instruct_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_coder_1.5b_instruct_q3_k_l +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_coder_1.5b_instruct_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_coder_1.5b_instruct_q3_k_l_en_5.5.1_3.0_1730258490977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_coder_1.5b_instruct_q3_k_l_en_5.5.1_3.0_1730258490977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_coder_1.5b_instruct_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_coder_1.5b_instruct_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_coder_1.5b_instruct_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|874.6 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-Coder-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q4_k_m_en.md new file mode 100644 index 00000000000000..c69ea2ba360b7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_coder_1.5b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_coder_1.5b_instruct_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_coder_1.5b_instruct_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_coder_1.5b_instruct_q4_k_m_en_5.5.1_3.0_1730258536773.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_coder_1.5b_instruct_q4_k_m_en_5.5.1_3.0_1730258536773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_coder_1.5b_instruct_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_coder_1.5b_instruct_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_coder_1.5b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|966.8 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-Coder-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q6_k_en.md new file mode 100644 index 00000000000000..62a7bc61fccc5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_coder_1.5b_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_coder_1.5b_instruct_q6_k +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_coder_1.5b_instruct_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_coder_1.5b_instruct_q6_k_en_5.5.1_3.0_1730258590883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_coder_1.5b_instruct_q6_k_en_5.5.1_3.0_1730258590883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_coder_1.5b_instruct_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_coder_1.5b_instruct_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_coder_1.5b_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-Coder-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q8_0_en.md new file mode 100644 index 00000000000000..1ff63323711567 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_coder_1.5b_instruct_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_coder_1.5b_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_coder_1.5b_instruct_q8_0 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_coder_1.5b_instruct_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_coder_1.5b_instruct_q8_0_en_5.5.1_3.0_1730258661015.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_coder_1.5b_instruct_q8_0_en_5.5.1_3.0_1730258661015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_coder_1.5b_instruct_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_coder_1.5b_instruct_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_coder_1.5b_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-Coder-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q3_k_l_en.md new file mode 100644 index 00000000000000..6f3fd80931d8cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_math_1.5b_instruct_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_math_1.5b_instruct_q3_k_l +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_math_1.5b_instruct_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_math_1.5b_instruct_q3_k_l_en_5.5.1_3.0_1730265177084.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_math_1.5b_instruct_q3_k_l_en_5.5.1_3.0_1730265177084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_math_1.5b_instruct_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_math_1.5b_instruct_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_math_1.5b_instruct_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|873.1 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q4_k_m_en.md new file mode 100644 index 00000000000000..1006e9ec404f20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_math_1.5b_instruct_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_math_1.5b_instruct_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_math_1.5b_instruct_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_math_1.5b_instruct_q4_k_m_en_5.5.1_3.0_1730265223021.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_math_1.5b_instruct_q4_k_m_en_5.5.1_3.0_1730265223021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_math_1.5b_instruct_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_math_1.5b_instruct_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_math_1.5b_instruct_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|965.4 MB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q6_k_en.md new file mode 100644 index 00000000000000..e724f5660e7789 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_math_1.5b_instruct_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_math_1.5b_instruct_q6_k +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_math_1.5b_instruct_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_math_1.5b_instruct_q6_k_en_5.5.1_3.0_1730265276620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_math_1.5b_instruct_q6_k_en_5.5.1_3.0_1730265276620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_math_1.5b_instruct_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_math_1.5b_instruct_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_math_1.5b_instruct_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q8_0_en.md new file mode 100644 index 00000000000000..aef024d3d20025 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-qwen2.5_math_1.5b_instruct_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English qwen2.5_math_1.5b_instruct_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: qwen2.5_math_1.5b_instruct_q8_0 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qwen2.5_math_1.5b_instruct_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qwen2.5_math_1.5b_instruct_q8_0_en_5.5.1_3.0_1730265348303.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qwen2.5_math_1.5b_instruct_q8_0_en_5.5.1_3.0_1730265348303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_math_1.5b_instruct_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("qwen2.5_math_1.5b_instruct_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qwen2.5_math_1.5b_instruct_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/lmstudio-community/Qwen2.5-Math-1.5B-Instruct-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-yi_1.5_6b_chat_q3_k_l_en.md b/docs/_posts/ahmedlone127/2024-10-30-yi_1.5_6b_chat_q3_k_l_en.md new file mode 100644 index 00000000000000..916f79e1afa12e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-yi_1.5_6b_chat_q3_k_l_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_1.5_6b_chat_q3_k_l AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_1.5_6b_chat_q3_k_l +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_1.5_6b_chat_q3_k_l` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_1.5_6b_chat_q3_k_l_en_5.5.1_3.0_1730262370878.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_1.5_6b_chat_q3_k_l_en_5.5.1_3.0_1730262370878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_1.5_6b_chat_q3_k_l","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_1.5_6b_chat_q3_k_l", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_1.5_6b_chat_q3_k_l| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.2 GB| + +## References + +https://huggingface.co/lmstudio-community/Yi-1.5-6B-Chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-yi_1.5_6b_chat_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-yi_1.5_6b_chat_q4_k_m_en.md new file mode 100644 index 00000000000000..a8e83a0d8aca6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-yi_1.5_6b_chat_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_1.5_6b_chat_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_1.5_6b_chat_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_1.5_6b_chat_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_1.5_6b_chat_q4_k_m_en_5.5.1_3.0_1730262528006.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_1.5_6b_chat_q4_k_m_en_5.5.1_3.0_1730262528006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_1.5_6b_chat_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_1.5_6b_chat_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_1.5_6b_chat_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|3.6 GB| + +## References + +https://huggingface.co/lmstudio-community/Yi-1.5-6B-Chat-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q4_0_4_4_en.md b/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q4_0_4_4_en.md new file mode 100644 index 00000000000000..8e6634c9be0f7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q4_0_4_4_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_coder_1.5b_q4_0_4_4 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_coder_1.5b_q4_0_4_4 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_coder_1.5b_q4_0_4_4` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_q4_0_4_4_en_5.5.1_3.0_1730259343634.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_q4_0_4_4_en_5.5.1_3.0_1730259343634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_q4_0_4_4","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_q4_0_4_4", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_coder_1.5b_q4_0_4_4| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|824.5 MB| + +## References + +https://huggingface.co/lmstudio-community/Yi-Coder-1.5B-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q4_k_m_en.md b/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q4_k_m_en.md new file mode 100644 index 00000000000000..e509984dd38a00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q4_k_m_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_coder_1.5b_q4_k_m AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_coder_1.5b_q4_k_m +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_coder_1.5b_q4_k_m` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_q4_k_m_en_5.5.1_3.0_1730259398913.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_q4_k_m_en_5.5.1_3.0_1730259398913.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_q4_k_m","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_q4_k_m", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_coder_1.5b_q4_k_m| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|944.8 MB| + +## References + +https://huggingface.co/lmstudio-community/Yi-Coder-1.5B-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q6_k_en.md b/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q6_k_en.md new file mode 100644 index 00000000000000..76a67c96cfc4c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q6_k_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_coder_1.5b_q6_k AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_coder_1.5b_q6_k +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_coder_1.5b_q6_k` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_q6_k_en_5.5.1_3.0_1730259462613.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_q6_k_en_5.5.1_3.0_1730259462613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_q6_k","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_q6_k", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_coder_1.5b_q6_k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/lmstudio-community/Yi-Coder-1.5B-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q8_0_en.md b/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q8_0_en.md new file mode 100644 index 00000000000000..9d9cdc82f447fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-10-30-yi_coder_1.5b_q8_0_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English yi_coder_1.5b_q8_0 AutoGGUFModel from lmstudio-community +author: John Snow Labs +name: yi_coder_1.5b_q8_0 +date: 2024-10-30 +tags: [en, open_source, onnx, conversational, text_generation, text_to_text, llamacpp] +task: Text Generation +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: llamacpp +annotator: AutoGGUFModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AutoGGUFModel model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`yi_coder_1.5b_q8_0` is a English model prepared by lmstudio-community. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_q8_0_en_5.5.1_3.0_1730259543780.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/yi_coder_1.5b_q8_0_en_5.5.1_3.0_1730259543780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_q8_0","en") \ + .setInputCols(["document"]) \ + .setOutputCol("completions") \ + .setBatchSize(4) \ + .setNPredict(20) \ + .setNGpuLayers(99) \ + .setTemperature(0.4) \ + .setTopK(40) \ + .setTopP(0.9) \ + .setPenalizeNl(True) + +pipeline = Pipeline().setStages([document, autoGGUFModel]) +data = spark.createDataFrame([["Hello, I am a"]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = False) + +``` +```scala + +val document = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val autoGGUFModel = AutoGGUFModel.pretrained("yi_coder_1.5b_q8_0", "en") + .setInputCols("document") + .setOutputCol("completions") + .setBatchSize(4) + .setNPredict(20) + .setNGpuLayers(99) + .setTemperature(0.4f) + .setTopK(40) + .setTopP(0.9f) + .setPenalizeNl(true) + +val pipeline = new Pipeline().setStages(Array(document, autoGGUFModel)) + +val data = Seq("Hello, I am a").toDF("text") +val result = pipeline.fit(data).transform(data) +result.select("completions").show(truncate = false) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|yi_coder_1.5b_q8_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[completions]| +|Language:|en| +|Size:|1.5 GB| + +## References + +https://huggingface.co/lmstudio-community/Yi-Coder-1.5B-GGUF \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-01-distilbart_xsum_12_6_en.md b/docs/_posts/ahmedlone127/2024-11-01-distilbart_xsum_12_6_en.md new file mode 100644 index 00000000000000..350a0b0646f51e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-01-distilbart_xsum_12_6_en.md @@ -0,0 +1,74 @@ +--- +layout: model +title: Abstractive Summarization by BART - DistilBART XSUM +author: John Snow Labs +name: distilbart_xsum_12_6 +date: 2024-11-01 +tags: [en, summarization, text_to_text, distil, open_source, openvino] +task: Summarization +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: BartTransformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +“BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension Transformer” The Facebook BART (Bidirectional and Auto-Regressive Transformer) model is a state-of-the-art language generation model that was introduced by Facebook AI in 2019. It is based on the transformer architecture and is designed to handle a wide range of natural language processing tasks such as text generation, summarization, and machine translation. + +This pre-trained model is DistilBART fine-tuned on the Extreme Summarization (XSum) Dataset. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_6_en_5.5.0_3.0_1730492024334.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbart_xsum_12_6_en_5.5.0_3.0_1730492024334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +bart = BartTransformer.pretrained("distilbart_xsum_12_6") \ + .setTask("summarize:") \ + .setMaxOutputLength(200) \ + .setInputCols(["documents"]) \ + .setOutputCol("summaries") +``` +```scala +val bart = BartTransformer.pretrained("distilbart_xsum_12_6") + .setTask("summarize:") + .setMaxOutputLength(200) + .setInputCols("documents") + .setOutputCol("summaries") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbart_xsum_12_6| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[generation]| +|Language:|en| +|Size:|853.7 MB| + +## References + +https://huggingface.co/sshleifer/distilbart-xsum-12-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-03-gpt2_en.md b/docs/_posts/ahmedlone127/2024-11-03-gpt2_en.md new file mode 100644 index 00000000000000..bd930b0c8484d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-03-gpt2_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: GPT2 text-to-text model (Base) +author: John Snow Labs +name: gpt2 +date: 2024-11-03 +tags: [gpt2, en, open_source, onnx, openvino] +task: Text Generation +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: openvino +annotator: GPT2Transformer +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +“GPT-2 displays a broad set of capabilities, including the ability to generate conditional synthetic text samples of unprecedented quality, where the model is primed with an input and it generates a lengthy continuation. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gpt2_en_5.5.0_3.0_1730653115205.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gpt2_en_5.5.0_3.0_1730653115205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ +.setInputCol("text") \ +.setOutputCol("documents") + +gpt2 = GPT2Transformer.pretrained("gpt2") \ +.setInputCols(["documents"]) \ +.setMaxOutputLength(50) \ +.setOutputCol("generation") + +pipeline = Pipeline().setStages([documentAssembler, gpt2]) +data = spark.createDataFrame([["My name is Leonardo."]]).toDF("text") +result = pipeline.fit(data).transform(data) +result.select("summaries.generation").show(truncate=False) +``` +```scala +val documentAssembler = new DocumentAssembler() +.setInputCol("text") +.setOutputCol("documents") + +val gpt2 = GPT2Transformer.pretrained("gpt2") +.setInputCols(Array("documents")) +.setMinOutputLength(10) +.setMaxOutputLength(50) +.setDoSample(false) +.setTopK(50) +.setNoRepeatNgramSize(3) +.setOutputCol("generation") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, gpt2)) + +val data = Seq("My name is Leonardo.").toDF("text") +val result = pipeline.fit(data).transform(data) +results.select("generation.result").show(truncate = false) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gpt2| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents]| +|Output Labels:|[generation]| +|Language:|en| +|Size:|467.4 MB| + +## References + +https://huggingface.co/openai-community/gpt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-08-hubert_large_japanese_asr_ja.md b/docs/_posts/ahmedlone127/2024-11-08-hubert_large_japanese_asr_ja.md new file mode 100644 index 00000000000000..179cb685bb018e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-08-hubert_large_japanese_asr_ja.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Japanese hubert_large_japanese_asr HubertForCTC from TKU410410103 +author: John Snow Labs +name: hubert_large_japanese_asr +date: 2024-11-08 +tags: [ja, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_large_japanese_asr` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_large_japanese_asr_ja_5.5.1_3.0_1731106819898.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_large_japanese_asr_ja_5.5.1_3.0_1731106819898.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 = HubertForCTC.pretrained("hubert_large_japanese_asr","ja") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("hubert_large_japanese_asr", "ja") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_large_japanese_asr| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ja| +|Size:|2.4 GB| + +## References + +https://huggingface.co/TKU410410103/hubert-large-japanese-asr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-08-hubert_large_japanese_asr_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-11-08-hubert_large_japanese_asr_pipeline_ja.md new file mode 100644 index 00000000000000..bbaf2cb1e9e949 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-08-hubert_large_japanese_asr_pipeline_ja.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Japanese hubert_large_japanese_asr_pipeline pipeline HubertForCTC from TKU410410103 +author: John Snow Labs +name: hubert_large_japanese_asr_pipeline +date: 2024-11-08 +tags: [ja, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_large_japanese_asr_pipeline` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_large_japanese_asr_pipeline_ja_5.5.1_3.0_1731106937966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_large_japanese_asr_pipeline_ja_5.5.1_3.0_1731106937966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hubert_large_japanese_asr_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hubert_large_japanese_asr_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_large_japanese_asr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|2.4 GB| + +## References + +https://huggingface.co/TKU410410103/hubert-large-japanese-asr + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-08-hubert_ukrainian_pipeline_uk.md b/docs/_posts/ahmedlone127/2024-11-08-hubert_ukrainian_pipeline_uk.md new file mode 100644 index 00000000000000..a7a707e6f4fca7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-08-hubert_ukrainian_pipeline_uk.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Ukrainian hubert_ukrainian_pipeline pipeline HubertForCTC from Yehor +author: John Snow Labs +name: hubert_ukrainian_pipeline +date: 2024-11-08 +tags: [uk, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: uk +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_ukrainian_pipeline` is a Ukrainian model originally trained by Yehor. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_ukrainian_pipeline_uk_5.5.1_3.0_1731106461400.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_ukrainian_pipeline_uk_5.5.1_3.0_1731106461400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hubert_ukrainian_pipeline", lang = "uk") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hubert_ukrainian_pipeline", lang = "uk") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_ukrainian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|uk| +|Size:|708.6 MB| + +## References + +https://huggingface.co/Yehor/hubert-uk + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-08-hubert_ukrainian_uk.md b/docs/_posts/ahmedlone127/2024-11-08-hubert_ukrainian_uk.md new file mode 100644 index 00000000000000..731f17518453aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-08-hubert_ukrainian_uk.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Ukrainian hubert_ukrainian HubertForCTC from Yehor +author: John Snow Labs +name: hubert_ukrainian +date: 2024-11-08 +tags: [uk, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: uk +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_ukrainian` is a Ukrainian model originally trained by Yehor. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_ukrainian_uk_5.5.1_3.0_1731106423734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_ukrainian_uk_5.5.1_3.0_1731106423734.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 = HubertForCTC.pretrained("hubert_ukrainian","uk") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("hubert_ukrainian", "uk") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_ukrainian| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|uk| +|Size:|708.6 MB| + +## References + +https://huggingface.co/Yehor/hubert-uk \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-08-unitku_hubert_japanese_asr_ja.md b/docs/_posts/ahmedlone127/2024-11-08-unitku_hubert_japanese_asr_ja.md new file mode 100644 index 00000000000000..2e5756e83f9213 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-08-unitku_hubert_japanese_asr_ja.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Japanese unitku_hubert_japanese_asr HubertForCTC from TKU410410103 +author: John Snow Labs +name: unitku_hubert_japanese_asr +date: 2024-11-08 +tags: [ja, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unitku_hubert_japanese_asr` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unitku_hubert_japanese_asr_ja_5.5.1_3.0_1731106577460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unitku_hubert_japanese_asr_ja_5.5.1_3.0_1731106577460.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 = HubertForCTC.pretrained("unitku_hubert_japanese_asr","ja") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("unitku_hubert_japanese_asr", "ja") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unitku_hubert_japanese_asr| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ja| +|Size:|708.5 MB| + +## References + +https://huggingface.co/TKU410410103/uniTKU-hubert-japanese-asr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-08-unitku_hubert_japanese_asr_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-11-08-unitku_hubert_japanese_asr_pipeline_ja.md new file mode 100644 index 00000000000000..04141277632332 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-08-unitku_hubert_japanese_asr_pipeline_ja.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Japanese unitku_hubert_japanese_asr_pipeline pipeline HubertForCTC from TKU410410103 +author: John Snow Labs +name: unitku_hubert_japanese_asr_pipeline +date: 2024-11-08 +tags: [ja, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unitku_hubert_japanese_asr_pipeline` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unitku_hubert_japanese_asr_pipeline_ja_5.5.1_3.0_1731106615568.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unitku_hubert_japanese_asr_pipeline_ja_5.5.1_3.0_1731106615568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("unitku_hubert_japanese_asr_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("unitku_hubert_japanese_asr_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unitku_hubert_japanese_asr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|708.5 MB| + +## References + +https://huggingface.co/TKU410410103/uniTKU-hubert-japanese-asr + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-afriberta_v2_large_en.md b/docs/_posts/ahmedlone127/2024-11-10-afriberta_v2_large_en.md new file mode 100644 index 00000000000000..c05c382dacc0a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-afriberta_v2_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English afriberta_v2_large XlmRoBertaEmbeddings from castorini +author: John Snow Labs +name: afriberta_v2_large +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_v2_large` is a English model originally trained by castorini. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_v2_large_en_5.5.1_3.0_1731282953480.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_v2_large_en_5.5.1_3.0_1731282953480.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") + +embeddings = XlmRoBertaEmbeddings.pretrained("afriberta_v2_large","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = XlmRoBertaEmbeddings.pretrained("afriberta_v2_large","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|afriberta_v2_large| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[xlm_roberta]| +|Language:|en| +|Size:|698.8 MB| + +## References + +https://huggingface.co/castorini/afriberta_v2_large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-afriberta_v2_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-afriberta_v2_large_pipeline_en.md new file mode 100644 index 00000000000000..c706a4fc12a106 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-afriberta_v2_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English afriberta_v2_large_pipeline pipeline XlmRoBertaEmbeddings from castorini +author: John Snow Labs +name: afriberta_v2_large_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`afriberta_v2_large_pipeline` is a English model originally trained by castorini. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/afriberta_v2_large_pipeline_en_5.5.1_3.0_1731282989499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/afriberta_v2_large_pipeline_en_5.5.1_3.0_1731282989499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("afriberta_v2_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("afriberta_v2_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|afriberta_v2_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|698.8 MB| + +## References + +https://huggingface.co/castorini/afriberta_v2_large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_base_chinese_finetuned_food_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_base_chinese_finetuned_food_en.md new file mode 100644 index 00000000000000..2d8838b6115ee7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_base_chinese_finetuned_food_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_food BertForTokenClassification from zhiguoxu +author: John Snow Labs +name: bert_base_chinese_finetuned_food +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_food` is a English model originally trained by zhiguoxu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_food_en_5.5.1_3.0_1731279799981.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_food_en_5.5.1_3.0_1731279799981.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_chinese_finetuned_food","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_chinese_finetuned_food", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_food| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|381.1 MB| + +## References + +https://huggingface.co/zhiguoxu/bert-base-chinese-finetuned-food \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_base_chinese_finetuned_food_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_base_chinese_finetuned_food_pipeline_en.md new file mode 100644 index 00000000000000..be5c05a93a5c0a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_base_chinese_finetuned_food_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_food_pipeline pipeline BertForTokenClassification from zhiguoxu +author: John Snow Labs +name: bert_base_chinese_finetuned_food_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_food_pipeline` is a English model originally trained by zhiguoxu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_food_pipeline_en_5.5.1_3.0_1731279819532.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_food_pipeline_en_5.5.1_3.0_1731279819532.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_finetuned_food_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_finetuned_food_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_food_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|381.2 MB| + +## References + +https://huggingface.co/zhiguoxu/bert-base-chinese-finetuned-food + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_arc_ner_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_arc_ner_en.md new file mode 100644 index 00000000000000..afb323f2bf853a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_arc_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_arc_ner BertForTokenClassification from nstrn-mo +author: John Snow Labs +name: bert_finetuned_arc_ner +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_arc_ner` is a English model originally trained by nstrn-mo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_arc_ner_en_5.5.1_3.0_1731279808777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_arc_ner_en_5.5.1_3.0_1731279808777.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_arc_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_arc_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_arc_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/nstrn-mo/bert-finetuned-arc-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_arc_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_arc_ner_pipeline_en.md new file mode 100644 index 00000000000000..8f413ddae5894e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_arc_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_arc_ner_pipeline pipeline BertForTokenClassification from nstrn-mo +author: John Snow Labs +name: bert_finetuned_arc_ner_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_arc_ner_pipeline` is a English model originally trained by nstrn-mo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_arc_ner_pipeline_en_5.5.1_3.0_1731279829261.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_arc_ner_pipeline_en_5.5.1_3.0_1731279829261.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_arc_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_arc_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_arc_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/nstrn-mo/bert-finetuned-arc-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_1_es.md b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_1_es.md new file mode 100644 index 00000000000000..0173b5a6811573 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_1_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish bert_finetuned_ner_1 BertForTokenClassification from paulrojasg +author: John Snow Labs +name: bert_finetuned_ner_1 +date: 2024-11-10 +tags: [es, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_1` is a Castilian, Spanish model originally trained by paulrojasg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_1_es_5.5.1_3.0_1731280287792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_1_es_5.5.1_3.0_1731280287792.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_1","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_1", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|403.7 MB| + +## References + +https://huggingface.co/paulrojasg/bert-finetuned-ner-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_1_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_1_pipeline_es.md new file mode 100644 index 00000000000000..e21dfec1b9689c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_1_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bert_finetuned_ner_1_pipeline pipeline BertForTokenClassification from paulrojasg +author: John Snow Labs +name: bert_finetuned_ner_1_pipeline +date: 2024-11-10 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_1_pipeline` is a Castilian, Spanish model originally trained by paulrojasg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_1_pipeline_es_5.5.1_3.0_1731280308250.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_1_pipeline_es_5.5.1_3.0_1731280308250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_1_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_1_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|403.7 MB| + +## References + +https://huggingface.co/paulrojasg/bert-finetuned-ner-1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_rob101z_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_rob101z_en.md new file mode 100644 index 00000000000000..2c03b7018bfce6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_rob101z_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner_rob101z BertForTokenClassification from rob101z +author: John Snow Labs +name: bert_finetuned_ner_rob101z +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_rob101z` is a English model originally trained by rob101z. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_rob101z_en_5.5.1_3.0_1731279543189.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_rob101z_en_5.5.1_3.0_1731279543189.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_rob101z","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_rob101z", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_rob101z| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/rob101z/bert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_rob101z_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_rob101z_pipeline_en.md new file mode 100644 index 00000000000000..9ec1a09873ac95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_finetuned_ner_rob101z_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_rob101z_pipeline pipeline BertForTokenClassification from rob101z +author: John Snow Labs +name: bert_finetuned_ner_rob101z_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_rob101z_pipeline` is a English model originally trained by rob101z. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_rob101z_pipeline_en_5.5.1_3.0_1731279564182.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_rob101z_pipeline_en_5.5.1_3.0_1731279564182.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_rob101z_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_rob101z_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_rob101z_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/rob101z/bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_los_muchachos_es.md b/docs/_posts/ahmedlone127/2024-11-10-bert_los_muchachos_es.md new file mode 100644 index 00000000000000..c0d63ee98f089d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_los_muchachos_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish bert_los_muchachos BertForTokenClassification from KPOETA +author: John Snow Labs +name: bert_los_muchachos +date: 2024-11-10 +tags: [es, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_los_muchachos` is a Castilian, Spanish model originally trained by KPOETA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_los_muchachos_es_5.5.1_3.0_1731279598269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_los_muchachos_es_5.5.1_3.0_1731279598269.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_los_muchachos","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_los_muchachos", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_los_muchachos| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|403.7 MB| + +## References + +https://huggingface.co/KPOETA/Bert-Los-Muchachos \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_los_muchachos_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-10-bert_los_muchachos_pipeline_es.md new file mode 100644 index 00000000000000..4ac0ca80f26209 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_los_muchachos_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bert_los_muchachos_pipeline pipeline BertForTokenClassification from KPOETA +author: John Snow Labs +name: bert_los_muchachos_pipeline +date: 2024-11-10 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_los_muchachos_pipeline` is a Castilian, Spanish model originally trained by KPOETA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_los_muchachos_pipeline_es_5.5.1_3.0_1731279619400.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_los_muchachos_pipeline_es_5.5.1_3.0_1731279619400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_los_muchachos_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_los_muchachos_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_los_muchachos_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|403.7 MB| + +## References + +https://huggingface.co/KPOETA/Bert-Los-Muchachos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_sliding_window_epoch_6_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_sliding_window_epoch_6_en.md new file mode 100644 index 00000000000000..b3ca1e54b82196 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_sliding_window_epoch_6_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_sliding_window_epoch_6 DistilBertForQuestionAnswering from Whalejay +author: John Snow Labs +name: bert_sliding_window_epoch_6 +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sliding_window_epoch_6` is a English model originally trained by Whalejay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sliding_window_epoch_6_en_5.5.1_3.0_1731281025243.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sliding_window_epoch_6_en_5.5.1_3.0_1731281025243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_sliding_window_epoch_6","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_sliding_window_epoch_6", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sliding_window_epoch_6| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/Whalejay/bert-sliding-window_epoch_6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_sliding_window_epoch_6_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_sliding_window_epoch_6_pipeline_en.md new file mode 100644 index 00000000000000..16bb03d623dc00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_sliding_window_epoch_6_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_sliding_window_epoch_6_pipeline pipeline DistilBertForQuestionAnswering from Whalejay +author: John Snow Labs +name: bert_sliding_window_epoch_6_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sliding_window_epoch_6_pipeline` is a English model originally trained by Whalejay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sliding_window_epoch_6_pipeline_en_5.5.1_3.0_1731281037766.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sliding_window_epoch_6_pipeline_en_5.5.1_3.0_1731281037766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sliding_window_epoch_6_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sliding_window_epoch_6_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sliding_window_epoch_6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/Whalejay/bert-sliding-window_epoch_6 + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_swahili_over_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_swahili_over_en.md new file mode 100644 index 00000000000000..8b6b48c91b4513 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_swahili_over_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_swahili_over DistilBertForQuestionAnswering from Whalejay +author: John Snow Labs +name: bert_swahili_over +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swahili_over` is a English model originally trained by Whalejay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swahili_over_en_5.5.1_3.0_1731280924764.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swahili_over_en_5.5.1_3.0_1731280924764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swahili_over","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swahili_over", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_swahili_over| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/Whalejay/bert-sw_over \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_swahili_over_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_swahili_over_pipeline_en.md new file mode 100644 index 00000000000000..ac0432cccb0cc5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_swahili_over_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_swahili_over_pipeline pipeline DistilBertForQuestionAnswering from Whalejay +author: John Snow Labs +name: bert_swahili_over_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swahili_over_pipeline` is a English model originally trained by Whalejay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swahili_over_pipeline_en_5.5.1_3.0_1731280937596.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swahili_over_pipeline_en_5.5.1_3.0_1731280937596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_swahili_over_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_swahili_over_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_swahili_over_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.8 MB| + +## References + +https://huggingface.co/Whalejay/bert-sw_over + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_swz_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_swz_en.md new file mode 100644 index 00000000000000..2b019e601c13a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_swz_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_swz DistilBertForQuestionAnswering from Whalejay +author: John Snow Labs +name: bert_swz +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swz` is a English model originally trained by Whalejay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swz_en_5.5.1_3.0_1731281145658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swz_en_5.5.1_3.0_1731281145658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swz","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("bert_swz", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_swz| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|243.4 MB| + +## References + +https://huggingface.co/Whalejay/bert-swz \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-bert_swz_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-bert_swz_pipeline_en.md new file mode 100644 index 00000000000000..7595fa99c7795a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-bert_swz_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_swz_pipeline pipeline DistilBertForQuestionAnswering from Whalejay +author: John Snow Labs +name: bert_swz_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_swz_pipeline` is a English model originally trained by Whalejay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_swz_pipeline_en_5.5.1_3.0_1731281158228.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_swz_pipeline_en_5.5.1_3.0_1731281158228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_swz_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_swz_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_swz_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|243.4 MB| + +## References + +https://huggingface.co/Whalejay/bert-swz + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_beetroot16_en.md b/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_beetroot16_en.md new file mode 100644 index 00000000000000..29eac96def0b44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_beetroot16_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English burmese_awesome_qa_model_beetroot16 DistilBertForQuestionAnswering from Beetroot16 +author: John Snow Labs +name: burmese_awesome_qa_model_beetroot16 +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_beetroot16` is a English model originally trained by Beetroot16. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_beetroot16_en_5.5.1_3.0_1731281058274.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_beetroot16_en_5.5.1_3.0_1731281058274.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_beetroot16","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_beetroot16", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_qa_model_beetroot16| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Beetroot16/my_awesome_qa_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_beetroot16_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_beetroot16_pipeline_en.md new file mode 100644 index 00000000000000..1cf48b643e61d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_beetroot16_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English burmese_awesome_qa_model_beetroot16_pipeline pipeline DistilBertForQuestionAnswering from Beetroot16 +author: John Snow Labs +name: burmese_awesome_qa_model_beetroot16_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_beetroot16_pipeline` is a English model originally trained by Beetroot16. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_beetroot16_pipeline_en_5.5.1_3.0_1731281071491.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_beetroot16_pipeline_en_5.5.1_3.0_1731281071491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_qa_model_beetroot16_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_beetroot16_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_qa_model_beetroot16_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Beetroot16/my_awesome_qa_model + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_real_jiakai_en.md b/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_real_jiakai_en.md new file mode 100644 index 00000000000000..e1a9afc8a81e7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_real_jiakai_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English burmese_awesome_qa_model_real_jiakai DistilBertForQuestionAnswering from real-jiakai +author: John Snow Labs +name: burmese_awesome_qa_model_real_jiakai +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_real_jiakai` is a English model originally trained by real-jiakai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_real_jiakai_en_5.5.1_3.0_1731281015961.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_real_jiakai_en_5.5.1_3.0_1731281015961.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_real_jiakai","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_awesome_qa_model_real_jiakai", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_qa_model_real_jiakai| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/real-jiakai/my_awesome_qa_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_real_jiakai_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_real_jiakai_pipeline_en.md new file mode 100644 index 00000000000000..18459187f13add --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-burmese_awesome_qa_model_real_jiakai_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English burmese_awesome_qa_model_real_jiakai_pipeline pipeline DistilBertForQuestionAnswering from real-jiakai +author: John Snow Labs +name: burmese_awesome_qa_model_real_jiakai_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_awesome_qa_model_real_jiakai_pipeline` is a English model originally trained by real-jiakai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_real_jiakai_pipeline_en_5.5.1_3.0_1731281028771.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_awesome_qa_model_real_jiakai_pipeline_en_5.5.1_3.0_1731281028771.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_awesome_qa_model_real_jiakai_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_awesome_qa_model_real_jiakai_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_awesome_qa_model_real_jiakai_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/real-jiakai/my_awesome_qa_model + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-burmese_first_model_en.md b/docs/_posts/ahmedlone127/2024-11-10-burmese_first_model_en.md new file mode 100644 index 00000000000000..b5a6842b2f4f85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-burmese_first_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English burmese_first_model DistilBertForQuestionAnswering from DarrenLo +author: John Snow Labs +name: burmese_first_model +date: 2024-11-10 +tags: [distilbert, en, open_source, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_model` is a English model originally trained by DarrenLo. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_model_en_5.5.1_3.0_1731280892050.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_model_en_5.5.1_3.0_1731280892050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + + +spanClassifier = DistilBertForQuestionAnswering.pretrained("burmese_first_model","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([document_assembler, spanClassifier]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) +``` +```scala +val document_assembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering + .pretrained("burmese_first_model", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_first_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +References + +References + +https://huggingface.co/DarrenLo/my_first_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-burmese_first_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-burmese_first_model_pipeline_en.md new file mode 100644 index 00000000000000..9a6fdad032b978 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-burmese_first_model_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English burmese_first_model_pipeline pipeline CamemBertEmbeddings from hippoleveque +author: John Snow Labs +name: burmese_first_model_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_first_model_pipeline` is a English model originally trained by hippoleveque. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_first_model_pipeline_en_5.5.1_3.0_1731280912722.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_first_model_pipeline_en_5.5.1_3.0_1731280912722.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("burmese_first_model_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("burmese_first_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_first_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +References + +https://huggingface.co/hippoleveque/my-first-model + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-camelbert_msa_qalb15_ged_13_ar.md b/docs/_posts/ahmedlone127/2024-11-10-camelbert_msa_qalb15_ged_13_ar.md new file mode 100644 index 00000000000000..d351ec03a5cc3f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-camelbert_msa_qalb15_ged_13_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic camelbert_msa_qalb15_ged_13 BertForTokenClassification from CAMeL-Lab +author: John Snow Labs +name: camelbert_msa_qalb15_ged_13 +date: 2024-11-10 +tags: [ar, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camelbert_msa_qalb15_ged_13` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camelbert_msa_qalb15_ged_13_ar_5.5.1_3.0_1731280259651.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camelbert_msa_qalb15_ged_13_ar_5.5.1_3.0_1731280259651.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') + +tokenClassifier = BertForTokenClassification.pretrained("camelbert_msa_qalb15_ged_13","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("camelbert_msa_qalb15_ged_13", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camelbert_msa_qalb15_ged_13| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|406.4 MB| + +## References + +https://huggingface.co/CAMeL-Lab/camelbert-msa-qalb15-ged-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-camelbert_msa_qalb15_ged_13_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-11-10-camelbert_msa_qalb15_ged_13_pipeline_ar.md new file mode 100644 index 00000000000000..446faf154ccd98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-camelbert_msa_qalb15_ged_13_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic camelbert_msa_qalb15_ged_13_pipeline pipeline BertForTokenClassification from CAMeL-Lab +author: John Snow Labs +name: camelbert_msa_qalb15_ged_13_pipeline +date: 2024-11-10 +tags: [ar, open_source, pipeline, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camelbert_msa_qalb15_ged_13_pipeline` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camelbert_msa_qalb15_ged_13_pipeline_ar_5.5.1_3.0_1731280281051.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camelbert_msa_qalb15_ged_13_pipeline_ar_5.5.1_3.0_1731280281051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("camelbert_msa_qalb15_ged_13_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("camelbert_msa_qalb15_ged_13_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camelbert_msa_qalb15_ged_13_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|406.4 MB| + +## References + +https://huggingface.co/CAMeL-Lab/camelbert-msa-qalb15-ged-13 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-camembert_base_fr.md b/docs/_posts/ahmedlone127/2024-11-10-camembert_base_fr.md new file mode 100644 index 00000000000000..c0161a8bb4ae32 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-camembert_base_fr.md @@ -0,0 +1,87 @@ +--- +layout: model +title: CamemBERT Base Model +author: John Snow Labs +name: camembert_base +date: 2024-11-10 +tags: [fr, french, embeddings, camembert, base, open_source, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +[CamemBERT](https://arxiv.org/abs/1911.03894) is a state-of-the-art language model for French based on the RoBERTa model. +For further information or requests, please go to [Camembert Website](https://camembert-model.fr/) + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_fr_5.5.1_3.0_1731281647430.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_fr_5.5.1_3.0_1731281647430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings = CamemBertEmbeddings.pretrained("camembert_base", "fr") \ +.setInputCols("sentence", "token") \ +.setOutputCol("embeddings") +``` +```scala +val embeddings = CamemBertEmbeddings.pretrained("camembert_base", "fr") +.setInputCols("sentence", "token") +.setOutputCol("embeddings") +``` + +{:.nlu-block} +```python +import nlu +nlu.load("fr.embed.camembert_base").predict("""Put your text here.""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_base| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|fr| +|Size:|264.0 MB| + +## Benchmarking + +```bash + + + +| Model | #params | Arch. | Training data | +|--------------------------------|--------------------------------|-------|-----------------------------------| +| `camembert-base` | 110M | Base | OSCAR (138 GB of text) | +| `camembert/camembert-large` | 335M | Large | CCNet (135 GB of text) | +| `camembert/camembert-base-ccnet` | 110M | Base | CCNet (135 GB of text) | +| `camembert/camembert-base-wikipedia-4gb` | 110M | Base | Wikipedia (4 GB of text) | +| `camembert/camembert-base-oscar-4gb` | 110M | Base | Subsample of OSCAR (4 GB of text) | +| `camembert/camembert-base-ccnet-4gb` | 110M | Base | Subsample of CCNet (4 GB of text) | +``` \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-camembert_base_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-11-10-camembert_base_pipeline_fr.md new file mode 100644 index 00000000000000..8cf3d53c32571e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-camembert_base_pipeline_fr.md @@ -0,0 +1,72 @@ +--- +layout: model +title: French camembert_base_pipeline pipeline CamemBertEmbeddings from almanach +author: John Snow Labs +name: camembert_base_pipeline +date: 2024-11-10 +tags: [fr, open_source, pipeline, onnx] +task: Embeddings +language: fr +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`camembert_base_pipeline` is a French model originally trained by almanach. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/camembert_base_pipeline_fr_5.5.1_3.0_1731281725493.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/camembert_base_pipeline_fr_5.5.1_3.0_1731281725493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("camembert_base_pipeline", lang = "fr") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("camembert_base_pipeline", lang = "fr") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|camembert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|264.0 MB| + +## References + +References + +https://huggingface.co/almanach/camembert-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-damage_trigger_effect_2024_11_06_13_00_en.md b/docs/_posts/ahmedlone127/2024-11-10-damage_trigger_effect_2024_11_06_13_00_en.md new file mode 100644 index 00000000000000..ae337e93852488 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-damage_trigger_effect_2024_11_06_13_00_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English damage_trigger_effect_2024_11_06_13_00 BertForTokenClassification from Lolimorimorf +author: John Snow Labs +name: damage_trigger_effect_2024_11_06_13_00 +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`damage_trigger_effect_2024_11_06_13_00` is a English model originally trained by Lolimorimorf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/damage_trigger_effect_2024_11_06_13_00_en_5.5.1_3.0_1731279661470.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/damage_trigger_effect_2024_11_06_13_00_en_5.5.1_3.0_1731279661470.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') + +tokenClassifier = BertForTokenClassification.pretrained("damage_trigger_effect_2024_11_06_13_00","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("damage_trigger_effect_2024_11_06_13_00", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|damage_trigger_effect_2024_11_06_13_00| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/Lolimorimorf/damage_trigger_effect_2024-11-06_13_00 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-damage_trigger_effect_2024_11_06_13_00_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-damage_trigger_effect_2024_11_06_13_00_pipeline_en.md new file mode 100644 index 00000000000000..2e66cbbe5009a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-damage_trigger_effect_2024_11_06_13_00_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English damage_trigger_effect_2024_11_06_13_00_pipeline pipeline BertForTokenClassification from Lolimorimorf +author: John Snow Labs +name: damage_trigger_effect_2024_11_06_13_00_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`damage_trigger_effect_2024_11_06_13_00_pipeline` is a English model originally trained by Lolimorimorf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/damage_trigger_effect_2024_11_06_13_00_pipeline_en_5.5.1_3.0_1731279697514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/damage_trigger_effect_2024_11_06_13_00_pipeline_en_5.5.1_3.0_1731279697514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("damage_trigger_effect_2024_11_06_13_00_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("damage_trigger_effect_2024_11_06_13_00_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|damage_trigger_effect_2024_11_06_13_00_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/Lolimorimorf/damage_trigger_effect_2024-11-06_13_00 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-devicebert_base_cased_v1_0_en.md b/docs/_posts/ahmedlone127/2024-11-10-devicebert_base_cased_v1_0_en.md new file mode 100644 index 00000000000000..0eece87f726985 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-devicebert_base_cased_v1_0_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English devicebert_base_cased_v1_0 BertForTokenClassification from mfarrington +author: John Snow Labs +name: devicebert_base_cased_v1_0 +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`devicebert_base_cased_v1_0` is a English model originally trained by mfarrington. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/devicebert_base_cased_v1_0_en_5.5.1_3.0_1731280029932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/devicebert_base_cased_v1_0_en_5.5.1_3.0_1731280029932.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') + +tokenClassifier = BertForTokenClassification.pretrained("devicebert_base_cased_v1_0","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("devicebert_base_cased_v1_0", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|devicebert_base_cased_v1_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|869.3 MB| + +## References + +https://huggingface.co/mfarrington/devicebert-base-cased-v1.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-devicebert_base_cased_v1_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-devicebert_base_cased_v1_0_pipeline_en.md new file mode 100644 index 00000000000000..93cd6048269de6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-devicebert_base_cased_v1_0_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English devicebert_base_cased_v1_0_pipeline pipeline BertForTokenClassification from mfarrington +author: John Snow Labs +name: devicebert_base_cased_v1_0_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`devicebert_base_cased_v1_0_pipeline` is a English model originally trained by mfarrington. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/devicebert_base_cased_v1_0_pipeline_en_5.5.1_3.0_1731280075380.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/devicebert_base_cased_v1_0_pipeline_en_5.5.1_3.0_1731280075380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("devicebert_base_cased_v1_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("devicebert_base_cased_v1_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|devicebert_base_cased_v1_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|869.3 MB| + +## References + +https://huggingface.co/mfarrington/devicebert-base-cased-v1.0 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_cotysong113_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_cotysong113_en.md new file mode 100644 index 00000000000000..9c462b20b8cb3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_cotysong113_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_imdb_cotysong113 DistilBertEmbeddings from cotysong113 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_imdb_cotysong113 +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, distilbert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +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.`distilbert_base_uncased_finetuned_imdb_cotysong113` is a English model originally trained by cotysong113. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cotysong113_en_5.5.1_3.0_1731282176150.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cotysong113_en_5.5.1_3.0_1731282176150.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") + +embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_cotysong113","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_cotysong113","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_imdb_cotysong113| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[distilbert]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/cotysong113/distilbert-base-uncased-finetuned-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline_en.md new file mode 100644 index 00000000000000..8d44d9e2fb7caa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline pipeline DistilBertEmbeddings from cotysong113 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline` is a English model originally trained by cotysong113. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline_en_5.5.1_3.0_1731282189190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline_en_5.5.1_3.0_1731282189190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_imdb_cotysong113_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/cotysong113/distilbert-base-uncased-finetuned-imdb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ehottl_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ehottl_en.md new file mode 100644 index 00000000000000..dbacb232bdbf60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ehottl_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_imdb_ehottl DistilBertEmbeddings from ehottl +author: John Snow Labs +name: distilbert_base_uncased_finetuned_imdb_ehottl +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, distilbert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +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.`distilbert_base_uncased_finetuned_imdb_ehottl` is a English model originally trained by ehottl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ehottl_en_5.5.1_3.0_1731282139864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ehottl_en_5.5.1_3.0_1731282139864.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") + +embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ehottl","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ehottl","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_imdb_ehottl| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[distilbert]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/ehottl/distilbert-base-uncased-finetuned-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ehottl_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ehottl_pipeline_en.md new file mode 100644 index 00000000000000..d39253c5f1987c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ehottl_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_imdb_ehottl_pipeline pipeline DistilBertEmbeddings from ehottl +author: John Snow Labs +name: distilbert_base_uncased_finetuned_imdb_ehottl_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ehottl_pipeline` is a English model originally trained by ehottl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ehottl_pipeline_en_5.5.1_3.0_1731282152676.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ehottl_pipeline_en_5.5.1_3.0_1731282152676.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ehottl_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ehottl_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_imdb_ehottl_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/ehottl/distilbert-base-uncased-finetuned-imdb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_gpragada_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_gpragada_en.md new file mode 100644 index 00000000000000..1b6ad6af277429 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_gpragada_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_imdb_gpragada DistilBertEmbeddings from Gpragada +author: John Snow Labs +name: distilbert_base_uncased_finetuned_imdb_gpragada +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, distilbert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +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.`distilbert_base_uncased_finetuned_imdb_gpragada` is a English model originally trained by Gpragada. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_gpragada_en_5.5.1_3.0_1731282229661.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_gpragada_en_5.5.1_3.0_1731282229661.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") + +embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_gpragada","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_gpragada","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_imdb_gpragada| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[distilbert]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Gpragada/distilbert-base-uncased-finetuned-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_gpragada_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_gpragada_pipeline_en.md new file mode 100644 index 00000000000000..5d6fec4b18237f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_gpragada_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_imdb_gpragada_pipeline pipeline DistilBertEmbeddings from Gpragada +author: John Snow Labs +name: distilbert_base_uncased_finetuned_imdb_gpragada_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_gpragada_pipeline` is a English model originally trained by Gpragada. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_gpragada_pipeline_en_5.5.1_3.0_1731282242420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_gpragada_pipeline_en_5.5.1_3.0_1731282242420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_gpragada_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_gpragada_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_imdb_gpragada_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Gpragada/distilbert-base-uncased-finetuned-imdb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ryosuke11_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ryosuke11_en.md new file mode 100644 index 00000000000000..6b8b9b137a7027 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ryosuke11_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_imdb_ryosuke11 DistilBertEmbeddings from Ryosuke11 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_imdb_ryosuke11 +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, distilbert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +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.`distilbert_base_uncased_finetuned_imdb_ryosuke11` is a English model originally trained by Ryosuke11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ryosuke11_en_5.5.1_3.0_1731282148349.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ryosuke11_en_5.5.1_3.0_1731282148349.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") + +embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ryosuke11","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_imdb_ryosuke11","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_imdb_ryosuke11| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[distilbert]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Ryosuke11/distilbert-base-uncased-finetuned-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline_en.md new file mode 100644 index 00000000000000..05bf063d4cfec5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline pipeline DistilBertEmbeddings from Ryosuke11 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline` is a English model originally trained by Ryosuke11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline_en_5.5.1_3.0_1731282161867.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline_en_5.5.1_3.0_1731282161867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_imdb_ryosuke11_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Ryosuke11/distilbert-base-uncased-finetuned-imdb + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_arthur2025_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_arthur2025_en.md new file mode 100644 index 00000000000000..f552a129fb20cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_arthur2025_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_squad_arthur2025 DistilBertForQuestionAnswering from Arthur2025 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_squad_arthur2025 +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_arthur2025` is a English model originally trained by Arthur2025. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_arthur2025_en_5.5.1_3.0_1731281054898.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_arthur2025_en_5.5.1_3.0_1731281054898.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_arthur2025","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_arthur2025", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_squad_arthur2025| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Arthur2025/distilbert-base-uncased-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_arthur2025_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_arthur2025_pipeline_en.md new file mode 100644 index 00000000000000..86b84e69ed083f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_arthur2025_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_squad_arthur2025_pipeline pipeline DistilBertForQuestionAnswering from Arthur2025 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_squad_arthur2025_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_arthur2025_pipeline` is a English model originally trained by Arthur2025. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_arthur2025_pipeline_en_5.5.1_3.0_1731281068086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_arthur2025_pipeline_en_5.5.1_3.0_1731281068086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_arthur2025_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_arthur2025_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_squad_arthur2025_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Arthur2025/distilbert-base-uncased-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_baranll0_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_baranll0_en.md new file mode 100644 index 00000000000000..67208a48302ea0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_baranll0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_squad_baranll0 DistilBertForQuestionAnswering from Baranll0 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_squad_baranll0 +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_baranll0` is a English model originally trained by Baranll0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_baranll0_en_5.5.1_3.0_1731280892679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_baranll0_en_5.5.1_3.0_1731280892679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_baranll0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_baranll0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_squad_baranll0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Baranll0/distilbert-base-uncased-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_baranll0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_baranll0_pipeline_en.md new file mode 100644 index 00000000000000..242222b3754520 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_baranll0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_squad_baranll0_pipeline pipeline DistilBertForQuestionAnswering from Baranll0 +author: John Snow Labs +name: distilbert_base_uncased_finetuned_squad_baranll0_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_baranll0_pipeline` is a English model originally trained by Baranll0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_baranll0_pipeline_en_5.5.1_3.0_1731280912515.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_baranll0_pipeline_en_5.5.1_3.0_1731280912515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_baranll0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_baranll0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_squad_baranll0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/Baranll0/distilbert-base-uncased-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_sprenkamp_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_sprenkamp_en.md new file mode 100644 index 00000000000000..3b12e654fdbf0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_sprenkamp_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_squad_sprenkamp DistilBertForQuestionAnswering from sprenkamp +author: John Snow Labs +name: distilbert_base_uncased_finetuned_squad_sprenkamp +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_sprenkamp` is a English model originally trained by sprenkamp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_sprenkamp_en_5.5.1_3.0_1731281165915.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_sprenkamp_en_5.5.1_3.0_1731281165915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_sprenkamp","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("distilbert_base_uncased_finetuned_squad_sprenkamp", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_squad_sprenkamp| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/sprenkamp/distilbert-base-uncased-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline_en.md new file mode 100644 index 00000000000000..76a4f7aeab72af --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline pipeline DistilBertForQuestionAnswering from sprenkamp +author: John Snow Labs +name: distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline` is a English model originally trained by sprenkamp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline_en_5.5.1_3.0_1731281178653.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline_en_5.5.1_3.0_1731281178653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_squad_sprenkamp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/sprenkamp/distilbert-base-uncased-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_toxicchat_accelerate_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_toxicchat_accelerate_en.md new file mode 100644 index 00000000000000..88a4771699ffe9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_toxicchat_accelerate_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_toxicchat_accelerate DistilBertEmbeddings from imcord +author: John Snow Labs +name: distilbert_base_uncased_finetuned_toxicchat_accelerate +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, distilbert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +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.`distilbert_base_uncased_finetuned_toxicchat_accelerate` is a English model originally trained by imcord. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_toxicchat_accelerate_en_5.5.1_3.0_1731282141997.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_toxicchat_accelerate_en_5.5.1_3.0_1731282141997.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") + +embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_toxicchat_accelerate","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DistilBertEmbeddings.pretrained("distilbert_base_uncased_finetuned_toxicchat_accelerate","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_toxicchat_accelerate| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[distilbert]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/imcord/distilbert-base-uncased-finetuned-toxicchat-accelerate \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline_en.md new file mode 100644 index 00000000000000..0ad94025c00a43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline pipeline DistilBertEmbeddings from imcord +author: John Snow Labs +name: distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline` is a English model originally trained by imcord. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline_en_5.5.1_3.0_1731282155311.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline_en_5.5.1_3.0_1731282155311.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_uncased_finetuned_toxicchat_accelerate_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/imcord/distilbert-base-uncased-finetuned-toxicchat-accelerate + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-dummy_model_minsik_oh_en.md b/docs/_posts/ahmedlone127/2024-11-10-dummy_model_minsik_oh_en.md new file mode 100644 index 00000000000000..0d860b9fd3fc62 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-dummy_model_minsik_oh_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_minsik_oh CamemBertEmbeddings from minsik-oh +author: John Snow Labs +name: dummy_model_minsik_oh +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_minsik_oh` is a English model originally trained by minsik-oh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_minsik_oh_en_5.5.1_3.0_1731281650536.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_minsik_oh_en_5.5.1_3.0_1731281650536.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") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_minsik_oh","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_minsik_oh","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_minsik_oh| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/minsik-oh/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-dummy_model_minsik_oh_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-dummy_model_minsik_oh_pipeline_en.md new file mode 100644 index 00000000000000..782b385cdd5450 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-dummy_model_minsik_oh_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_minsik_oh_pipeline pipeline CamemBertEmbeddings from minsik-oh +author: John Snow Labs +name: dummy_model_minsik_oh_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_minsik_oh_pipeline` is a English model originally trained by minsik-oh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_minsik_oh_pipeline_en_5.5.1_3.0_1731281727740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_minsik_oh_pipeline_en_5.5.1_3.0_1731281727740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_minsik_oh_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_minsik_oh_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_minsik_oh_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/minsik-oh/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-dummy_model_osanseviero_en.md b/docs/_posts/ahmedlone127/2024-11-10-dummy_model_osanseviero_en.md new file mode 100644 index 00000000000000..c400ea64cd7572 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-dummy_model_osanseviero_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English dummy_model_osanseviero CamemBertEmbeddings from osanseviero +author: John Snow Labs +name: dummy_model_osanseviero +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, camembert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CamemBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_osanseviero` is a English model originally trained by osanseviero. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_osanseviero_en_5.5.1_3.0_1731281750854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_osanseviero_en_5.5.1_3.0_1731281750854.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") + +embeddings = CamemBertEmbeddings.pretrained("dummy_model_osanseviero","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = CamemBertEmbeddings.pretrained("dummy_model_osanseviero","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_osanseviero| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[camembert]| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/osanseviero/dummy-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-dummy_model_osanseviero_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-dummy_model_osanseviero_pipeline_en.md new file mode 100644 index 00000000000000..3bc3689c116572 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-dummy_model_osanseviero_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English dummy_model_osanseviero_pipeline pipeline CamemBertEmbeddings from osanseviero +author: John Snow Labs +name: dummy_model_osanseviero_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CamemBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dummy_model_osanseviero_pipeline` is a English model originally trained by osanseviero. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dummy_model_osanseviero_pipeline_en_5.5.1_3.0_1731281825605.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dummy_model_osanseviero_pipeline_en_5.5.1_3.0_1731281825605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("dummy_model_osanseviero_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("dummy_model_osanseviero_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dummy_model_osanseviero_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|264.0 MB| + +## References + +https://huggingface.co/osanseviero/dummy-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- CamemBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-duplicate1_en.md b/docs/_posts/ahmedlone127/2024-11-10-duplicate1_en.md new file mode 100644 index 00000000000000..1c57689a92c63c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-duplicate1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English duplicate1 BertForTokenClassification from Somisetty2347 +author: John Snow Labs +name: duplicate1 +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`duplicate1` is a English model originally trained by Somisetty2347. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/duplicate1_en_5.5.1_3.0_1731280110525.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/duplicate1_en_5.5.1_3.0_1731280110525.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') + +tokenClassifier = BertForTokenClassification.pretrained("duplicate1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("duplicate1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|duplicate1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/Somisetty2347/duplicate1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-duplicate1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-duplicate1_pipeline_en.md new file mode 100644 index 00000000000000..256abcf0431f60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-duplicate1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English duplicate1_pipeline pipeline BertForTokenClassification from Somisetty2347 +author: John Snow Labs +name: duplicate1_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`duplicate1_pipeline` is a English model originally trained by Somisetty2347. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/duplicate1_pipeline_en_5.5.1_3.0_1731280134766.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/duplicate1_pipeline_en_5.5.1_3.0_1731280134766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("duplicate1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("duplicate1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|duplicate1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.4 MB| + +## References + +https://huggingface.co/Somisetty2347/duplicate1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-finetuned_bert_chinese_base_en.md b/docs/_posts/ahmedlone127/2024-11-10-finetuned_bert_chinese_base_en.md new file mode 100644 index 00000000000000..b997cad0590ceb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-finetuned_bert_chinese_base_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_bert_chinese_base BertForTokenClassification from r45289 +author: John Snow Labs +name: finetuned_bert_chinese_base +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_chinese_base` is a English model originally trained by r45289. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_chinese_base_en_5.5.1_3.0_1731279959385.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_chinese_base_en_5.5.1_3.0_1731279959385.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') + +tokenClassifier = BertForTokenClassification.pretrained("finetuned_bert_chinese_base","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("finetuned_bert_chinese_base", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_chinese_base| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|381.1 MB| + +## References + +https://huggingface.co/r45289/finetuned-bert-chinese-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-finetuned_bert_chinese_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-finetuned_bert_chinese_base_pipeline_en.md new file mode 100644 index 00000000000000..364fc96fd407cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-finetuned_bert_chinese_base_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_bert_chinese_base_pipeline pipeline BertForTokenClassification from r45289 +author: John Snow Labs +name: finetuned_bert_chinese_base_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_chinese_base_pipeline` is a English model originally trained by r45289. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_chinese_base_pipeline_en_5.5.1_3.0_1731279980123.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_chinese_base_pipeline_en_5.5.1_3.0_1731279980123.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_bert_chinese_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_bert_chinese_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_chinese_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|381.1 MB| + +## References + +https://huggingface.co/r45289/finetuned-bert-chinese-base + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-german_medical_ner_de.md b/docs/_posts/ahmedlone127/2024-11-10-german_medical_ner_de.md new file mode 100644 index 00000000000000..aab353afee4e70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-german_medical_ner_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German german_medical_ner BertForTokenClassification from HUMADEX +author: John Snow Labs +name: german_medical_ner +date: 2024-11-10 +tags: [de, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_medical_ner` is a German model originally trained by HUMADEX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_medical_ner_de_5.5.1_3.0_1731280121721.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_medical_ner_de_5.5.1_3.0_1731280121721.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') + +tokenClassifier = BertForTokenClassification.pretrained("german_medical_ner","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("german_medical_ner", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_medical_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|403.7 MB| + +## References + +https://huggingface.co/HUMADEX/german_medical_ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-german_medical_ner_pipeline_de.md b/docs/_posts/ahmedlone127/2024-11-10-german_medical_ner_pipeline_de.md new file mode 100644 index 00000000000000..c0ef2c609f6c85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-german_medical_ner_pipeline_de.md @@ -0,0 +1,70 @@ +--- +layout: model +title: German german_medical_ner_pipeline pipeline BertForTokenClassification from HUMADEX +author: John Snow Labs +name: german_medical_ner_pipeline +date: 2024-11-10 +tags: [de, open_source, pipeline, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_medical_ner_pipeline` is a German model originally trained by HUMADEX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_medical_ner_pipeline_de_5.5.1_3.0_1731280146620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_medical_ner_pipeline_de_5.5.1_3.0_1731280146620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("german_medical_ner_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("german_medical_ner_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_medical_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|403.7 MB| + +## References + +https://huggingface.co/HUMADEX/german_medical_ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-ijelid_indobertweet_en.md b/docs/_posts/ahmedlone127/2024-11-10-ijelid_indobertweet_en.md new file mode 100644 index 00000000000000..c8e6cb67895d7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-ijelid_indobertweet_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ijelid_indobertweet BertForTokenClassification from fathan +author: John Snow Labs +name: ijelid_indobertweet +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ijelid_indobertweet` is a English model originally trained by fathan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ijelid_indobertweet_en_5.5.1_3.0_1731279940333.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ijelid_indobertweet_en_5.5.1_3.0_1731279940333.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') + +tokenClassifier = BertForTokenClassification.pretrained("ijelid_indobertweet","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("ijelid_indobertweet", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ijelid_indobertweet| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|411.8 MB| + +## References + +https://huggingface.co/fathan/ijelid-indobertweet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-ijelid_indobertweet_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-ijelid_indobertweet_pipeline_en.md new file mode 100644 index 00000000000000..8f87aadc297849 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-ijelid_indobertweet_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ijelid_indobertweet_pipeline pipeline BertForTokenClassification from fathan +author: John Snow Labs +name: ijelid_indobertweet_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ijelid_indobertweet_pipeline` is a English model originally trained by fathan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ijelid_indobertweet_pipeline_en_5.5.1_3.0_1731279965018.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ijelid_indobertweet_pipeline_en_5.5.1_3.0_1731279965018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ijelid_indobertweet_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ijelid_indobertweet_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ijelid_indobertweet_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/fathan/ijelid-indobertweet + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-indobert_large_p2_finetuned_ner_id.md b/docs/_posts/ahmedlone127/2024-11-10-indobert_large_p2_finetuned_ner_id.md new file mode 100644 index 00000000000000..9932e9305b0ce3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-indobert_large_p2_finetuned_ner_id.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Indonesian indobert_large_p2_finetuned_ner BertForTokenClassification from ageng-anugrah +author: John Snow Labs +name: indobert_large_p2_finetuned_ner +date: 2024-11-10 +tags: [id, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: id +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_large_p2_finetuned_ner` is a Indonesian model originally trained by ageng-anugrah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_ner_id_5.5.1_3.0_1731279404489.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_ner_id_5.5.1_3.0_1731279404489.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') + +tokenClassifier = BertForTokenClassification.pretrained("indobert_large_p2_finetuned_ner","id") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("indobert_large_p2_finetuned_ner", "id") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_large_p2_finetuned_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|id| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ageng-anugrah/indobert-large-p2-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-indobert_large_p2_finetuned_ner_pipeline_id.md b/docs/_posts/ahmedlone127/2024-11-10-indobert_large_p2_finetuned_ner_pipeline_id.md new file mode 100644 index 00000000000000..fb086b30fb1fba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-indobert_large_p2_finetuned_ner_pipeline_id.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Indonesian indobert_large_p2_finetuned_ner_pipeline pipeline BertForTokenClassification from ageng-anugrah +author: John Snow Labs +name: indobert_large_p2_finetuned_ner_pipeline +date: 2024-11-10 +tags: [id, open_source, pipeline, onnx] +task: Named Entity Recognition +language: id +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_large_p2_finetuned_ner_pipeline` is a Indonesian model originally trained by ageng-anugrah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_ner_pipeline_id_5.5.1_3.0_1731279467948.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_large_p2_finetuned_ner_pipeline_id_5.5.1_3.0_1731279467948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indobert_large_p2_finetuned_ner_pipeline", lang = "id") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indobert_large_p2_finetuned_ner_pipeline", lang = "id") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_large_p2_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|id| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ageng-anugrah/indobert-large-p2-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-inhibitor_distilbert_en.md b/docs/_posts/ahmedlone127/2024-11-10-inhibitor_distilbert_en.md new file mode 100644 index 00000000000000..92db8c91100ed4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-inhibitor_distilbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English inhibitor_distilbert DistilBertEmbeddings from tonytonfisk +author: John Snow Labs +name: inhibitor_distilbert +date: 2024-11-10 +tags: [en, open_source, onnx, embeddings, distilbert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +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.`inhibitor_distilbert` is a English model originally trained by tonytonfisk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/inhibitor_distilbert_en_5.5.1_3.0_1731282144663.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inhibitor_distilbert_en_5.5.1_3.0_1731282144663.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") + +embeddings = DistilBertEmbeddings.pretrained("inhibitor_distilbert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val embeddings = DistilBertEmbeddings.pretrained("inhibitor_distilbert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|inhibitor_distilbert| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[distilbert]| +|Language:|en| +|Size:|248.3 MB| + +## References + +https://huggingface.co/tonytonfisk/inhibitor_distilbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-inhibitor_distilbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-inhibitor_distilbert_pipeline_en.md new file mode 100644 index 00000000000000..aa43c9100a1a97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-inhibitor_distilbert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English inhibitor_distilbert_pipeline pipeline DistilBertEmbeddings from tonytonfisk +author: John Snow Labs +name: inhibitor_distilbert_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`inhibitor_distilbert_pipeline` is a English model originally trained by tonytonfisk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/inhibitor_distilbert_pipeline_en_5.5.1_3.0_1731282159228.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/inhibitor_distilbert_pipeline_en_5.5.1_3.0_1731282159228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("inhibitor_distilbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("inhibitor_distilbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|inhibitor_distilbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|248.3 MB| + +## References + +https://huggingface.co/tonytonfisk/inhibitor_distilbert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DistilBertEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-mbert_finnic_ner_en.md b/docs/_posts/ahmedlone127/2024-11-10-mbert_finnic_ner_en.md new file mode 100644 index 00000000000000..8eb7b5f888f5bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-mbert_finnic_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mbert_finnic_ner BertForTokenClassification from azizbarank +author: John Snow Labs +name: mbert_finnic_ner +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_finnic_ner` is a English model originally trained by azizbarank. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_finnic_ner_en_5.5.1_3.0_1731279727500.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_finnic_ner_en_5.5.1_3.0_1731279727500.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') + +tokenClassifier = BertForTokenClassification.pretrained("mbert_finnic_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("mbert_finnic_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbert_finnic_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/azizbarank/mbert-finnic-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-mbert_finnic_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-mbert_finnic_ner_pipeline_en.md new file mode 100644 index 00000000000000..2739e5fab7efce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-mbert_finnic_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mbert_finnic_ner_pipeline pipeline BertForTokenClassification from azizbarank +author: John Snow Labs +name: mbert_finnic_ner_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_finnic_ner_pipeline` is a English model originally trained by azizbarank. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_finnic_ner_pipeline_en_5.5.1_3.0_1731279762269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_finnic_ner_pipeline_en_5.5.1_3.0_1731279762269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mbert_finnic_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mbert_finnic_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbert_finnic_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/azizbarank/mbert-finnic-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-medlid_en.md b/docs/_posts/ahmedlone127/2024-11-10-medlid_en.md new file mode 100644 index 00000000000000..e65ad60dda99c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-medlid_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English medlid BertForTokenClassification from onionLad +author: John Snow Labs +name: medlid +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medlid` is a English model originally trained by onionLad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medlid_en_5.5.1_3.0_1731280081924.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medlid_en_5.5.1_3.0_1731280081924.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') + +tokenClassifier = BertForTokenClassification.pretrained("medlid","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("medlid", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medlid| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/onionLad/medlid \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-medlid_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-medlid_pipeline_en.md new file mode 100644 index 00000000000000..f3b2c8473fd975 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-medlid_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English medlid_pipeline pipeline BertForTokenClassification from onionLad +author: John Snow Labs +name: medlid_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`medlid_pipeline` is a English model originally trained by onionLad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/medlid_pipeline_en_5.5.1_3.0_1731280109992.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/medlid_pipeline_en_5.5.1_3.0_1731280109992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("medlid_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("medlid_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|medlid_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/onionLad/medlid + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-mountains_ner_model_en.md b/docs/_posts/ahmedlone127/2024-11-10-mountains_ner_model_en.md new file mode 100644 index 00000000000000..a8bd812e360179 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-mountains_ner_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mountains_ner_model BertForTokenClassification from telord +author: John Snow Labs +name: mountains_ner_model +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mountains_ner_model` is a English model originally trained by telord. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mountains_ner_model_en_5.5.1_3.0_1731279562174.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mountains_ner_model_en_5.5.1_3.0_1731279562174.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') + +tokenClassifier = BertForTokenClassification.pretrained("mountains_ner_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("mountains_ner_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mountains_ner_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/telord/mountains-ner-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-mountains_ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-mountains_ner_model_pipeline_en.md new file mode 100644 index 00000000000000..43c12707a31381 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-mountains_ner_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mountains_ner_model_pipeline pipeline BertForTokenClassification from telord +author: John Snow Labs +name: mountains_ner_model_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mountains_ner_model_pipeline` is a English model originally trained by telord. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mountains_ner_model_pipeline_en_5.5.1_3.0_1731279587775.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mountains_ner_model_pipeline_en_5.5.1_3.0_1731279587775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mountains_ner_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mountains_ner_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mountains_ner_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/telord/mountains-ner-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-ner_rubert_finetuned_en.md b/docs/_posts/ahmedlone127/2024-11-10-ner_rubert_finetuned_en.md new file mode 100644 index 00000000000000..a005f107af75df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-ner_rubert_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ner_rubert_finetuned BertForTokenClassification from FlewRr +author: John Snow Labs +name: ner_rubert_finetuned +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_rubert_finetuned` is a English model originally trained by FlewRr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_rubert_finetuned_en_5.5.1_3.0_1731279899847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_rubert_finetuned_en_5.5.1_3.0_1731279899847.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') + +tokenClassifier = BertForTokenClassification.pretrained("ner_rubert_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("ner_rubert_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_rubert_finetuned| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|667.1 MB| + +## References + +https://huggingface.co/FlewRr/NER-ruBert-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-ner_rubert_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-ner_rubert_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..da687be5bd50ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-ner_rubert_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_rubert_finetuned_pipeline pipeline BertForTokenClassification from FlewRr +author: John Snow Labs +name: ner_rubert_finetuned_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_rubert_finetuned_pipeline` is a English model originally trained by FlewRr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_rubert_finetuned_pipeline_en_5.5.1_3.0_1731279936268.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_rubert_finetuned_pipeline_en_5.5.1_3.0_1731279936268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_rubert_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_rubert_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_rubert_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|667.1 MB| + +## References + +https://huggingface.co/FlewRr/NER-ruBert-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-nucha_itskillner_bert_en.md b/docs/_posts/ahmedlone127/2024-11-10-nucha_itskillner_bert_en.md new file mode 100644 index 00000000000000..bb497d4f96f9c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-nucha_itskillner_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nucha_itskillner_bert BertForTokenClassification from Nucha +author: John Snow Labs +name: nucha_itskillner_bert +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nucha_itskillner_bert` is a English model originally trained by Nucha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nucha_itskillner_bert_en_5.5.1_3.0_1731279445449.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nucha_itskillner_bert_en_5.5.1_3.0_1731279445449.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') + +tokenClassifier = BertForTokenClassification.pretrained("nucha_itskillner_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("nucha_itskillner_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nucha_itskillner_bert| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Nucha/Nucha_ITSkillNER_BERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-nucha_itskillner_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-nucha_itskillner_bert_pipeline_en.md new file mode 100644 index 00000000000000..fee995d1a8a977 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-nucha_itskillner_bert_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nucha_itskillner_bert_pipeline pipeline BertForTokenClassification from Nucha +author: John Snow Labs +name: nucha_itskillner_bert_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nucha_itskillner_bert_pipeline` is a English model originally trained by Nucha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nucha_itskillner_bert_pipeline_en_5.5.1_3.0_1731279466576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nucha_itskillner_bert_pipeline_en_5.5.1_3.0_1731279466576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nucha_itskillner_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nucha_itskillner_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nucha_itskillner_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Nucha/Nucha_ITSkillNER_BERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-pii_mbert_azerbaijani_en.md b/docs/_posts/ahmedlone127/2024-11-10-pii_mbert_azerbaijani_en.md new file mode 100644 index 00000000000000..4121771e83fe48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-pii_mbert_azerbaijani_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English pii_mbert_azerbaijani BertForTokenClassification from toghrultahirov +author: John Snow Labs +name: pii_mbert_azerbaijani +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_mbert_azerbaijani` is a English model originally trained by toghrultahirov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pii_mbert_azerbaijani_en_5.5.1_3.0_1731280115377.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_mbert_azerbaijani_en_5.5.1_3.0_1731280115377.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') + +tokenClassifier = BertForTokenClassification.pretrained("pii_mbert_azerbaijani","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("pii_mbert_azerbaijani", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pii_mbert_azerbaijani| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|625.5 MB| + +## References + +https://huggingface.co/toghrultahirov/pii_mbert_az \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-pii_mbert_azerbaijani_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-pii_mbert_azerbaijani_pipeline_en.md new file mode 100644 index 00000000000000..47e34e24c9e9fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-pii_mbert_azerbaijani_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English pii_mbert_azerbaijani_pipeline pipeline BertForTokenClassification from toghrultahirov +author: John Snow Labs +name: pii_mbert_azerbaijani_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pii_mbert_azerbaijani_pipeline` is a English model originally trained by toghrultahirov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pii_mbert_azerbaijani_pipeline_en_5.5.1_3.0_1731280155707.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pii_mbert_azerbaijani_pipeline_en_5.5.1_3.0_1731280155707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pii_mbert_azerbaijani_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pii_mbert_azerbaijani_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pii_mbert_azerbaijani_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|625.6 MB| + +## References + +https://huggingface.co/toghrultahirov/pii_mbert_az + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-practica_3_model_en.md b/docs/_posts/ahmedlone127/2024-11-10-practica_3_model_en.md new file mode 100644 index 00000000000000..5935bf05c5eecb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-practica_3_model_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English practica_3_model DistilBertForQuestionAnswering from Almancy +author: John Snow Labs +name: practica_3_model +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`practica_3_model` is a English model originally trained by Almancy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/practica_3_model_en_5.5.1_3.0_1731280883866.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/practica_3_model_en_5.5.1_3.0_1731280883866.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("practica_3_model","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("practica_3_model", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|practica_3_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Almancy/practica_3_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-practica_3_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-practica_3_model_pipeline_en.md new file mode 100644 index 00000000000000..f3301ae884f6ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-practica_3_model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English practica_3_model_pipeline pipeline DistilBertForQuestionAnswering from Almancy +author: John Snow Labs +name: practica_3_model_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`practica_3_model_pipeline` is a English model originally trained by Almancy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/practica_3_model_pipeline_en_5.5.1_3.0_1731280897108.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/practica_3_model_pipeline_en_5.5.1_3.0_1731280897108.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("practica_3_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("practica_3_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|practica_3_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/Almancy/practica_3_model + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-queryner_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2024-11-10-queryner_bert_base_uncased_en.md new file mode 100644 index 00000000000000..731545bfff3292 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-queryner_bert_base_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English queryner_bert_base_uncased BertForTokenClassification from bltlab +author: John Snow Labs +name: queryner_bert_base_uncased +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`queryner_bert_base_uncased` is a English model originally trained by bltlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/queryner_bert_base_uncased_en_5.5.1_3.0_1731279498347.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/queryner_bert_base_uncased_en_5.5.1_3.0_1731279498347.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') + +tokenClassifier = BertForTokenClassification.pretrained("queryner_bert_base_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("queryner_bert_base_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|queryner_bert_base_uncased| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/bltlab/queryner-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-queryner_bert_base_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-queryner_bert_base_uncased_pipeline_en.md new file mode 100644 index 00000000000000..16cdd03ed7df0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-queryner_bert_base_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English queryner_bert_base_uncased_pipeline pipeline BertForTokenClassification from bltlab +author: John Snow Labs +name: queryner_bert_base_uncased_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`queryner_bert_base_uncased_pipeline` is a English model originally trained by bltlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/queryner_bert_base_uncased_pipeline_en_5.5.1_3.0_1731279519243.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/queryner_bert_base_uncased_pipeline_en_5.5.1_3.0_1731279519243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("queryner_bert_base_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("queryner_bert_base_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|queryner_bert_base_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/bltlab/queryner-bert-base-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-rubert_address_elements_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-11-10-rubert_address_elements_pipeline_ru.md new file mode 100644 index 00000000000000..bf04cac1e49356 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-rubert_address_elements_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian rubert_address_elements_pipeline pipeline BertForTokenClassification from qwazer +author: John Snow Labs +name: rubert_address_elements_pipeline +date: 2024-11-10 +tags: [ru, open_source, pipeline, onnx] +task: Named Entity Recognition +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_address_elements_pipeline` is a Russian model originally trained by qwazer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_address_elements_pipeline_ru_5.5.1_3.0_1731279362868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_address_elements_pipeline_ru_5.5.1_3.0_1731279362868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rubert_address_elements_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rubert_address_elements_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_address_elements_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|109.2 MB| + +## References + +https://huggingface.co/qwazer/rubert-address-elements + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-rubert_address_elements_ru.md b/docs/_posts/ahmedlone127/2024-11-10-rubert_address_elements_ru.md new file mode 100644 index 00000000000000..9a577a3f530fe8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-rubert_address_elements_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian rubert_address_elements BertForTokenClassification from qwazer +author: John Snow Labs +name: rubert_address_elements +date: 2024-11-10 +tags: [ru, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_address_elements` is a Russian model originally trained by qwazer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_address_elements_ru_5.5.1_3.0_1731279357401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_address_elements_ru_5.5.1_3.0_1731279357401.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') + +tokenClassifier = BertForTokenClassification.pretrained("rubert_address_elements","ru") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("rubert_address_elements", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_address_elements| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ru| +|Size:|109.1 MB| + +## References + +https://huggingface.co/qwazer/rubert-address-elements \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-sent_afriberta_v2_large_en.md b/docs/_posts/ahmedlone127/2024-11-10-sent_afriberta_v2_large_en.md new file mode 100644 index 00000000000000..af1a42765e9735 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-sent_afriberta_v2_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_afriberta_v2_large XlmRoBertaSentenceEmbeddings from castorini +author: John Snow Labs +name: sent_afriberta_v2_large +date: 2024-11-10 +tags: [en, open_source, onnx, sentence_embeddings, xlm_roberta] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afriberta_v2_large` is a English model originally trained by castorini. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afriberta_v2_large_en_5.5.1_3.0_1731282587875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afriberta_v2_large_en_5.5.1_3.0_1731282587875.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afriberta_v2_large","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = XlmRoBertaSentenceEmbeddings.pretrained("sent_afriberta_v2_large","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_afriberta_v2_large| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|698.8 MB| + +## References + +https://huggingface.co/castorini/afriberta_v2_large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-sent_afriberta_v2_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-sent_afriberta_v2_large_pipeline_en.md new file mode 100644 index 00000000000000..c960cb84a67faa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-sent_afriberta_v2_large_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_afriberta_v2_large_pipeline pipeline XlmRoBertaSentenceEmbeddings from castorini +author: John Snow Labs +name: sent_afriberta_v2_large_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_afriberta_v2_large_pipeline` is a English model originally trained by castorini. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_afriberta_v2_large_pipeline_en_5.5.1_3.0_1731282623156.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_afriberta_v2_large_pipeline_en_5.5.1_3.0_1731282623156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_afriberta_v2_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_afriberta_v2_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_afriberta_v2_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|699.3 MB| + +## References + +https://huggingface.co/castorini/afriberta_v2_large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- XlmRoBertaSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-social_bias_ner_en.md b/docs/_posts/ahmedlone127/2024-11-10-social_bias_ner_en.md new file mode 100644 index 00000000000000..5211ed4e32043b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-social_bias_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English social_bias_ner BertForTokenClassification from ethical-spectacle +author: John Snow Labs +name: social_bias_ner +date: 2024-11-10 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`social_bias_ner` is a English model originally trained by ethical-spectacle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/social_bias_ner_en_5.5.1_3.0_1731279695568.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/social_bias_ner_en_5.5.1_3.0_1731279695568.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') + +tokenClassifier = BertForTokenClassification.pretrained("social_bias_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("social_bias_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|social_bias_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/ethical-spectacle/social-bias-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-social_bias_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-social_bias_ner_pipeline_en.md new file mode 100644 index 00000000000000..145a52b8e042c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-social_bias_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English social_bias_ner_pipeline pipeline BertForTokenClassification from ethical-spectacle +author: John Snow Labs +name: social_bias_ner_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`social_bias_ner_pipeline` is a English model originally trained by ethical-spectacle. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/social_bias_ner_pipeline_en_5.5.1_3.0_1731279717050.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/social_bias_ner_pipeline_en_5.5.1_3.0_1731279717050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("social_bias_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("social_bias_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|social_bias_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/ethical-spectacle/social-bias-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-training_distilbert_base_uncased_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-11-10-training_distilbert_base_uncased_finetuned_squad_en.md new file mode 100644 index 00000000000000..1ac813bf6eeed4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-training_distilbert_base_uncased_finetuned_squad_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English training_distilbert_base_uncased_finetuned_squad DistilBertForQuestionAnswering from lizchu414 +author: John Snow Labs +name: training_distilbert_base_uncased_finetuned_squad +date: 2024-11-10 +tags: [en, open_source, onnx, question_answering, distilbert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`training_distilbert_base_uncased_finetuned_squad` is a English model originally trained by lizchu414. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/training_distilbert_base_uncased_finetuned_squad_en_5.5.1_3.0_1731280892071.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/training_distilbert_base_uncased_finetuned_squad_en_5.5.1_3.0_1731280892071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = DistilBertForQuestionAnswering.pretrained("training_distilbert_base_uncased_finetuned_squad","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering.pretrained("training_distilbert_base_uncased_finetuned_squad", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|training_distilbert_base_uncased_finetuned_squad| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|247.2 MB| + +## References + +https://huggingface.co/lizchu414/training-distilbert-base-uncased-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-10-training_distilbert_base_uncased_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-10-training_distilbert_base_uncased_finetuned_squad_pipeline_en.md new file mode 100644 index 00000000000000..4e86ecff7fe32c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-10-training_distilbert_base_uncased_finetuned_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English training_distilbert_base_uncased_finetuned_squad_pipeline pipeline DistilBertForQuestionAnswering from lizchu414 +author: John Snow Labs +name: training_distilbert_base_uncased_finetuned_squad_pipeline +date: 2024-11-10 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`training_distilbert_base_uncased_finetuned_squad_pipeline` is a English model originally trained by lizchu414. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/training_distilbert_base_uncased_finetuned_squad_pipeline_en_5.5.1_3.0_1731280905863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/training_distilbert_base_uncased_finetuned_squad_pipeline_en_5.5.1_3.0_1731280905863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("training_distilbert_base_uncased_finetuned_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("training_distilbert_base_uncased_finetuned_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|training_distilbert_base_uncased_finetuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|247.3 MB| + +## References + +https://huggingface.co/lizchu414/training-distilbert-base-uncased-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- DistilBertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-4248_spanbert_base_en.md b/docs/_posts/ahmedlone127/2024-11-11-4248_spanbert_base_en.md new file mode 100644 index 00000000000000..fab5242f737d5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-4248_spanbert_base_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English 4248_spanbert_base BertForQuestionAnswering from JMatthewChiam +author: John Snow Labs +name: 4248_spanbert_base +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`4248_spanbert_base` is a English model originally trained by JMatthewChiam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/4248_spanbert_base_en_5.5.1_3.0_1731288773376.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/4248_spanbert_base_en_5.5.1_3.0_1731288773376.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("4248_spanbert_base","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("4248_spanbert_base", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|4248_spanbert_base| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|402.9 MB| + +## References + +https://huggingface.co/JMatthewChiam/4248-spanBERT-Base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-4248_spanbert_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-4248_spanbert_base_pipeline_en.md new file mode 100644 index 00000000000000..ee07cc7489f981 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-4248_spanbert_base_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English 4248_spanbert_base_pipeline pipeline BertForQuestionAnswering from JMatthewChiam +author: John Snow Labs +name: 4248_spanbert_base_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`4248_spanbert_base_pipeline` is a English model originally trained by JMatthewChiam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/4248_spanbert_base_pipeline_en_5.5.1_3.0_1731288794996.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/4248_spanbert_base_pipeline_en_5.5.1_3.0_1731288794996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("4248_spanbert_base_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("4248_spanbert_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|4248_spanbert_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|402.9 MB| + +## References + +https://huggingface.co/JMatthewChiam/4248-spanBERT-Base + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-affilgood_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-affilgood_ner_en.md new file mode 100644 index 00000000000000..8af9a2eeb5fc6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-affilgood_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English affilgood_ner RoBertaForTokenClassification from SIRIS-Lab +author: John Snow Labs +name: affilgood_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`affilgood_ner` is a English model originally trained by SIRIS-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/affilgood_ner_en_5.5.1_3.0_1731311681436.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/affilgood_ner_en_5.5.1_3.0_1731311681436.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("affilgood_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("affilgood_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|affilgood_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|466.1 MB| + +## References + +https://huggingface.co/SIRIS-Lab/affilgood-NER \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-affilgood_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-affilgood_ner_pipeline_en.md new file mode 100644 index 00000000000000..7c40efccefdad7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-affilgood_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English affilgood_ner_pipeline pipeline RoBertaForTokenClassification from SIRIS-Lab +author: John Snow Labs +name: affilgood_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`affilgood_ner_pipeline` is a English model originally trained by SIRIS-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/affilgood_ner_pipeline_en_5.5.1_3.0_1731311706201.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/affilgood_ner_pipeline_en_5.5.1_3.0_1731311706201.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("affilgood_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("affilgood_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|affilgood_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.1 MB| + +## References + +https://huggingface.co/SIRIS-Lab/affilgood-NER + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-albert_dataset1_en.md b/docs/_posts/ahmedlone127/2024-11-11-albert_dataset1_en.md new file mode 100644 index 00000000000000..8f4626395f9975 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-albert_dataset1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English albert_dataset1 AlbertForSequenceClassification from aminajunaid0 +author: John Snow Labs +name: albert_dataset1 +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_dataset1` is a English model originally trained by aminajunaid0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_dataset1_en_5.5.1_3.0_1731296925732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_dataset1_en_5.5.1_3.0_1731296925732.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 = AlbertForSequenceClassification.pretrained("albert_dataset1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("albert_dataset1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_dataset1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/aminajunaid0/Albert_Dataset1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-albert_dataset1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-albert_dataset1_pipeline_en.md new file mode 100644 index 00000000000000..4c0b7e573eb04c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-albert_dataset1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English albert_dataset1_pipeline pipeline AlbertForSequenceClassification from aminajunaid0 +author: John Snow Labs +name: albert_dataset1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`albert_dataset1_pipeline` is a English model originally trained by aminajunaid0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/albert_dataset1_pipeline_en_5.5.1_3.0_1731296927971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/albert_dataset1_pipeline_en_5.5.1_3.0_1731296927971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("albert_dataset1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("albert_dataset1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|albert_dataset1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/aminajunaid0/Albert_Dataset1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-alephbertgimmel_parashoot_he.md b/docs/_posts/ahmedlone127/2024-11-11-alephbertgimmel_parashoot_he.md new file mode 100644 index 00000000000000..036f0606d08beb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-alephbertgimmel_parashoot_he.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Hebrew alephbertgimmel_parashoot BertForQuestionAnswering from imvladikon +author: John Snow Labs +name: alephbertgimmel_parashoot +date: 2024-11-11 +tags: [he, open_source, onnx, question_answering, bert] +task: Question Answering +language: he +edition: Spark NLP 5.5.1 +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.`alephbertgimmel_parashoot` is a Hebrew model originally trained by imvladikon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alephbertgimmel_parashoot_he_5.5.1_3.0_1731289180085.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alephbertgimmel_parashoot_he_5.5.1_3.0_1731289180085.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("alephbertgimmel_parashoot","he") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("alephbertgimmel_parashoot", "he") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alephbertgimmel_parashoot| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|he| +|Size:|690.4 MB| + +## References + +https://huggingface.co/imvladikon/alephbertgimmel_parashoot \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-alephbertgimmel_parashoot_pipeline_he.md b/docs/_posts/ahmedlone127/2024-11-11-alephbertgimmel_parashoot_pipeline_he.md new file mode 100644 index 00000000000000..ead148507c6574 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-alephbertgimmel_parashoot_pipeline_he.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Hebrew alephbertgimmel_parashoot_pipeline pipeline BertForQuestionAnswering from imvladikon +author: John Snow Labs +name: alephbertgimmel_parashoot_pipeline +date: 2024-11-11 +tags: [he, open_source, pipeline, onnx] +task: Question Answering +language: he +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`alephbertgimmel_parashoot_pipeline` is a Hebrew model originally trained by imvladikon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/alephbertgimmel_parashoot_pipeline_he_5.5.1_3.0_1731289217381.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/alephbertgimmel_parashoot_pipeline_he_5.5.1_3.0_1731289217381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("alephbertgimmel_parashoot_pipeline", lang = "he") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("alephbertgimmel_parashoot_pipeline", lang = "he") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|alephbertgimmel_parashoot_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|he| +|Size:|690.5 MB| + +## References + +https://huggingface.co/imvladikon/alephbertgimmel_parashoot + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-all_mpnet_base_v2_tomaarsen_en.md b/docs/_posts/ahmedlone127/2024-11-11-all_mpnet_base_v2_tomaarsen_en.md new file mode 100644 index 00000000000000..af9dac29e9219b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-all_mpnet_base_v2_tomaarsen_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English all_mpnet_base_v2_tomaarsen MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: all_mpnet_base_v2_tomaarsen +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_tomaarsen` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tomaarsen_en_5.5.1_3.0_1731295094969.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tomaarsen_en_5.5.1_3.0_1731295094969.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") + +embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_tomaarsen","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("all_mpnet_base_v2_tomaarsen","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_tomaarsen| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/tomaarsen/all-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-all_mpnet_base_v2_tomaarsen_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-all_mpnet_base_v2_tomaarsen_pipeline_en.md new file mode 100644 index 00000000000000..05d6ac0d199286 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-all_mpnet_base_v2_tomaarsen_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English all_mpnet_base_v2_tomaarsen_pipeline pipeline MPNetEmbeddings from tomaarsen +author: John Snow Labs +name: all_mpnet_base_v2_tomaarsen_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`all_mpnet_base_v2_tomaarsen_pipeline` is a English model originally trained by tomaarsen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tomaarsen_pipeline_en_5.5.1_3.0_1731295120658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/all_mpnet_base_v2_tomaarsen_pipeline_en_5.5.1_3.0_1731295120658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("all_mpnet_base_v2_tomaarsen_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("all_mpnet_base_v2_tomaarsen_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|all_mpnet_base_v2_tomaarsen_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/tomaarsen/all-mpnet-base-v2 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-aspect_based_sentiment_analyzer_using_bert_en.md b/docs/_posts/ahmedlone127/2024-11-11-aspect_based_sentiment_analyzer_using_bert_en.md new file mode 100644 index 00000000000000..ab80e5ab9f3e0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-aspect_based_sentiment_analyzer_using_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English aspect_based_sentiment_analyzer_using_bert BertForSequenceClassification from srimeenakshiks +author: John Snow Labs +name: aspect_based_sentiment_analyzer_using_bert +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`aspect_based_sentiment_analyzer_using_bert` is a English model originally trained by srimeenakshiks. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/aspect_based_sentiment_analyzer_using_bert_en_5.5.1_3.0_1731309636675.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/aspect_based_sentiment_analyzer_using_bert_en_5.5.1_3.0_1731309636675.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("aspect_based_sentiment_analyzer_using_bert","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("aspect_based_sentiment_analyzer_using_bert", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|aspect_based_sentiment_analyzer_using_bert| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/srimeenakshiks/aspect-based-sentiment-analyzer-using-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-auto_adver_en.md b/docs/_posts/ahmedlone127/2024-11-11-auto_adver_en.md new file mode 100644 index 00000000000000..acb4e1755b83d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-auto_adver_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English auto_adver BertForTokenClassification from Phil-AT +author: John Snow Labs +name: auto_adver +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`auto_adver` is a English model originally trained by Phil-AT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/auto_adver_en_5.5.1_3.0_1731299498613.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/auto_adver_en_5.5.1_3.0_1731299498613.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') + +tokenClassifier = BertForTokenClassification.pretrained("auto_adver","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("auto_adver", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|auto_adver| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Phil-AT/Auto-Adver \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-auto_adver_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-auto_adver_pipeline_en.md new file mode 100644 index 00000000000000..1ba9a77efacb57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-auto_adver_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English auto_adver_pipeline pipeline BertForTokenClassification from Phil-AT +author: John Snow Labs +name: auto_adver_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`auto_adver_pipeline` is a English model originally trained by Phil-AT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/auto_adver_pipeline_en_5.5.1_3.0_1731299561942.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/auto_adver_pipeline_en_5.5.1_3.0_1731299561942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("auto_adver_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("auto_adver_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|auto_adver_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Phil-AT/Auto-Adver + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-autotrain_gamblingtips_43804110844_en.md b/docs/_posts/ahmedlone127/2024-11-11-autotrain_gamblingtips_43804110844_en.md new file mode 100644 index 00000000000000..4dea1d91bc0d82 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-autotrain_gamblingtips_43804110844_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English autotrain_gamblingtips_43804110844 BertForQuestionAnswering from Berrisaur +author: John Snow Labs +name: autotrain_gamblingtips_43804110844 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`autotrain_gamblingtips_43804110844` is a English model originally trained by Berrisaur. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_gamblingtips_43804110844_en_5.5.1_3.0_1731289457467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_gamblingtips_43804110844_en_5.5.1_3.0_1731289457467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("autotrain_gamblingtips_43804110844","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("autotrain_gamblingtips_43804110844", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_gamblingtips_43804110844| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Berrisaur/autotrain-gamblingtips-43804110844 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-autotrain_gamblingtips_43804110844_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-autotrain_gamblingtips_43804110844_pipeline_en.md new file mode 100644 index 00000000000000..a5ad5671bbf392 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-autotrain_gamblingtips_43804110844_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English autotrain_gamblingtips_43804110844_pipeline pipeline BertForQuestionAnswering from Berrisaur +author: John Snow Labs +name: autotrain_gamblingtips_43804110844_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_gamblingtips_43804110844_pipeline` is a English model originally trained by Berrisaur. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_gamblingtips_43804110844_pipeline_en_5.5.1_3.0_1731289523769.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_gamblingtips_43804110844_pipeline_en_5.5.1_3.0_1731289523769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_gamblingtips_43804110844_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_gamblingtips_43804110844_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_gamblingtips_43804110844_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Berrisaur/autotrain-gamblingtips-43804110844 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-autotrain_nzog3_ca819_en.md b/docs/_posts/ahmedlone127/2024-11-11-autotrain_nzog3_ca819_en.md new file mode 100644 index 00000000000000..289dcdde1404d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-autotrain_nzog3_ca819_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English autotrain_nzog3_ca819 MPNetForSequenceClassification from ulisesbravo +author: John Snow Labs +name: autotrain_nzog3_ca819 +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_nzog3_ca819` is a English model originally trained by ulisesbravo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_nzog3_ca819_en_5.5.1_3.0_1731301504833.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_nzog3_ca819_en_5.5.1_3.0_1731301504833.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 = MPNetForSequenceClassification.pretrained("autotrain_nzog3_ca819","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("autotrain_nzog3_ca819", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_nzog3_ca819| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.0 MB| + +## References + +https://huggingface.co/ulisesbravo/autotrain-nzog3-ca819 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-autotrain_nzog3_ca819_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-autotrain_nzog3_ca819_pipeline_en.md new file mode 100644 index 00000000000000..7b5800c54a6b56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-autotrain_nzog3_ca819_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English autotrain_nzog3_ca819_pipeline pipeline MPNetForSequenceClassification from ulisesbravo +author: John Snow Labs +name: autotrain_nzog3_ca819_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_nzog3_ca819_pipeline` is a English model originally trained by ulisesbravo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_nzog3_ca819_pipeline_en_5.5.1_3.0_1731301527188.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_nzog3_ca819_pipeline_en_5.5.1_3.0_1731301527188.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("autotrain_nzog3_ca819_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("autotrain_nzog3_ca819_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_nzog3_ca819_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.0 MB| + +## References + +https://huggingface.co/ulisesbravo/autotrain-nzog3-ca819 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-banglabert_qa_en.md b/docs/_posts/ahmedlone127/2024-11-11-banglabert_qa_en.md new file mode 100644 index 00000000000000..d6f037773497a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-banglabert_qa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English banglabert_qa BertForQuestionAnswering from sanzanalora +author: John Snow Labs +name: banglabert_qa +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`banglabert_qa` is a English model originally trained by sanzanalora. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/banglabert_qa_en_5.5.1_3.0_1731307694600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/banglabert_qa_en_5.5.1_3.0_1731307694600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("banglabert_qa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("banglabert_qa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|banglabert_qa| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/sanzanalora/banglabert-qa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-banglabert_qa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-banglabert_qa_pipeline_en.md new file mode 100644 index 00000000000000..d3a3acf3d80a0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-banglabert_qa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English banglabert_qa_pipeline pipeline BertForQuestionAnswering from sanzanalora +author: John Snow Labs +name: banglabert_qa_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`banglabert_qa_pipeline` is a English model originally trained by sanzanalora. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/banglabert_qa_pipeline_en_5.5.1_3.0_1731307717699.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/banglabert_qa_pipeline_en_5.5.1_3.0_1731307717699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("banglabert_qa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("banglabert_qa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|banglabert_qa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/sanzanalora/banglabert-qa + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_340m_ft_first_1000_pref_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_340m_ft_first_1000_pref_en.md new file mode 100644 index 00000000000000..9fa6307ce1f59f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_340m_ft_first_1000_pref_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_340m_ft_first_1000_pref BertForSequenceClassification from SeppeV +author: John Snow Labs +name: bert_340m_ft_first_1000_pref +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_340m_ft_first_1000_pref` is a English model originally trained by SeppeV. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_340m_ft_first_1000_pref_en_5.5.1_3.0_1731309886322.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_340m_ft_first_1000_pref_en_5.5.1_3.0_1731309886322.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_340m_ft_first_1000_pref","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_340m_ft_first_1000_pref", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_340m_ft_first_1000_pref| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/SeppeV/bert_340M_ft_first_1000_pref \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_340m_ft_first_1000_pref_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_340m_ft_first_1000_pref_pipeline_en.md new file mode 100644 index 00000000000000..d2d9ac3c3a8b08 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_340m_ft_first_1000_pref_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_340m_ft_first_1000_pref_pipeline pipeline BertForSequenceClassification from SeppeV +author: John Snow Labs +name: bert_340m_ft_first_1000_pref_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_340m_ft_first_1000_pref_pipeline` is a English model originally trained by SeppeV. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_340m_ft_first_1000_pref_pipeline_en_5.5.1_3.0_1731309950078.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_340m_ft_first_1000_pref_pipeline_en_5.5.1_3.0_1731309950078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_340m_ft_first_1000_pref_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_340m_ft_first_1000_pref_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_340m_ft_first_1000_pref_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/SeppeV/bert_340M_ft_first_1000_pref + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_abbrev_cased_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_abbrev_cased_en.md new file mode 100644 index 00000000000000..6c7e0b4259682b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_abbrev_cased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_abbrev_cased BertForTokenClassification from batterydata +author: John Snow Labs +name: bert_abbrev_cased +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_abbrev_cased` is a English model originally trained by batterydata. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_abbrev_cased_en_5.5.1_3.0_1731290509572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_abbrev_cased_en_5.5.1_3.0_1731290509572.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_abbrev_cased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_abbrev_cased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_abbrev_cased| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.6 MB| + +## References + +https://huggingface.co/batterydata/bert-abbrev-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_abbrev_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_abbrev_cased_pipeline_en.md new file mode 100644 index 00000000000000..7b6f92646d60e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_abbrev_cased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_abbrev_cased_pipeline pipeline BertForTokenClassification from batterydata +author: John Snow Labs +name: bert_abbrev_cased_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_abbrev_cased_pipeline` is a English model originally trained by batterydata. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_abbrev_cased_pipeline_en_5.5.1_3.0_1731290530928.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_abbrev_cased_pipeline_en_5.5.1_3.0_1731290530928.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_abbrev_cased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_abbrev_cased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_abbrev_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.6 MB| + +## References + +https://huggingface.co/batterydata/bert-abbrev-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_arabert_bioner_english_arabic_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_arabert_bioner_english_arabic_en.md new file mode 100644 index 00000000000000..4920bbd7f432f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_arabert_bioner_english_arabic_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_arabert_bioner_english_arabic BertForTokenClassification from StivenLancheros +author: John Snow Labs +name: bert_base_arabert_bioner_english_arabic +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabert_bioner_english_arabic` is a English model originally trained by StivenLancheros. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabert_bioner_english_arabic_en_5.5.1_3.0_1731286022889.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabert_bioner_english_arabic_en_5.5.1_3.0_1731286022889.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_arabert_bioner_english_arabic","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_arabert_bioner_english_arabic", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabert_bioner_english_arabic| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|504.6 MB| + +## References + +https://huggingface.co/StivenLancheros/bert-base-arabert-BioNER-EN-AR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_arabert_bioner_english_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_arabert_bioner_english_arabic_pipeline_en.md new file mode 100644 index 00000000000000..ae57ca59e1ee70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_arabert_bioner_english_arabic_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_arabert_bioner_english_arabic_pipeline pipeline BertForTokenClassification from StivenLancheros +author: John Snow Labs +name: bert_base_arabert_bioner_english_arabic_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabert_bioner_english_arabic_pipeline` is a English model originally trained by StivenLancheros. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabert_bioner_english_arabic_pipeline_en_5.5.1_3.0_1731286049165.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabert_bioner_english_arabic_pipeline_en_5.5.1_3.0_1731286049165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_arabert_bioner_english_arabic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_arabert_bioner_english_arabic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabert_bioner_english_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|504.6 MB| + +## References + +https://huggingface.co/StivenLancheros/bert-base-arabert-BioNER-EN-AR + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_finetuned_ner_en.md new file mode 100644 index 00000000000000..d7fdba3275af57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_finetuned_ner BertForTokenClassification from yuridrcosta +author: John Snow Labs +name: bert_base_cased_finetuned_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_ner` is a English model originally trained by yuridrcosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ner_en_5.5.1_3.0_1731298877348.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ner_en_5.5.1_3.0_1731298877348.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_cased_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_cased_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/yuridrcosta/bert-base-cased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..859cf1160e45d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_finetuned_ner_pipeline pipeline BertForTokenClassification from yuridrcosta +author: John Snow Labs +name: bert_base_cased_finetuned_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_ner_pipeline` is a English model originally trained by yuridrcosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ner_pipeline_en_5.5.1_3.0_1731298898561.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_ner_pipeline_en_5.5.1_3.0_1731298898561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/yuridrcosta/bert-base-cased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_mnli_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_mnli_en.md new file mode 100644 index 00000000000000..a4d2055afcc2b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_mnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_cased_mnli BertForSequenceClassification from WillHeld +author: John Snow Labs +name: bert_base_cased_mnli +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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` is a English model originally trained by WillHeld. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_en_5.5.1_3.0_1731309647852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_en_5.5.1_3.0_1731309647852.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_base_cased_mnli","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_mnli", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_mnli| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/WillHeld/bert-base-cased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_mnli_pipeline_en.md new file mode 100644 index 00000000000000..fcab768f11c4fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_cased_mnli_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_cased_mnli_pipeline pipeline BertForSequenceClassification from WillHeld +author: John Snow Labs +name: bert_base_cased_mnli_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_mnli_pipeline` is a English model originally trained by WillHeld. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_pipeline_en_5.5.1_3.0_1731309670318.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_pipeline_en_5.5.1_3.0_1731309670318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_cased_mnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_cased_mnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_mnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/WillHeld/bert-base-cased-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_chinese_finetuned_ner_v1_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_chinese_finetuned_ner_v1_en.md new file mode 100644 index 00000000000000..05b7da45abe151 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_chinese_finetuned_ner_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_ner_v1 BertForTokenClassification from leonadase +author: John Snow Labs +name: bert_base_chinese_finetuned_ner_v1 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_ner_v1` is a English model originally trained by leonadase. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_ner_v1_en_5.5.1_3.0_1731290477549.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_ner_v1_en_5.5.1_3.0_1731290477549.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_chinese_finetuned_ner_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_chinese_finetuned_ner_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_ner_v1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|381.1 MB| + +## References + +https://huggingface.co/leonadase/bert-base-chinese-finetuned-ner-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_chinese_finetuned_ner_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_chinese_finetuned_ner_v1_pipeline_en.md new file mode 100644 index 00000000000000..8049ea6a29d62a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_chinese_finetuned_ner_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_ner_v1_pipeline pipeline BertForTokenClassification from leonadase +author: John Snow Labs +name: bert_base_chinese_finetuned_ner_v1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_ner_v1_pipeline` is a English model originally trained by leonadase. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_ner_v1_pipeline_en_5.5.1_3.0_1731290498443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_ner_v1_pipeline_en_5.5.1_3.0_1731290498443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_chinese_finetuned_ner_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_chinese_finetuned_ner_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_ner_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|381.1 MB| + +## References + +https://huggingface.co/leonadase/bert-base-chinese-finetuned-ner-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_spanish_wwm_cased_ehealth_kd_es.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_spanish_wwm_cased_ehealth_kd_es.md new file mode 100644 index 00000000000000..63ce36af42d090 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_spanish_wwm_cased_ehealth_kd_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish bert_base_spanish_wwm_cased_ehealth_kd BertForTokenClassification from IIC +author: John Snow Labs +name: bert_base_spanish_wwm_cased_ehealth_kd +date: 2024-11-11 +tags: [es, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_ehealth_kd` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_ehealth_kd_es_5.5.1_3.0_1731290730612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_ehealth_kd_es_5.5.1_3.0_1731290730612.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_spanish_wwm_cased_ehealth_kd","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_spanish_wwm_cased_ehealth_kd", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_ehealth_kd| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|409.5 MB| + +## References + +https://huggingface.co/IIC/bert-base-spanish-wwm-cased-ehealth_kd \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_spanish_wwm_cased_ehealth_kd_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_spanish_wwm_cased_ehealth_kd_pipeline_es.md new file mode 100644 index 00000000000000..2ea3f926e3ea7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_spanish_wwm_cased_ehealth_kd_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bert_base_spanish_wwm_cased_ehealth_kd_pipeline pipeline BertForTokenClassification from IIC +author: John Snow Labs +name: bert_base_spanish_wwm_cased_ehealth_kd_pipeline +date: 2024-11-11 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_ehealth_kd_pipeline` is a Castilian, Spanish model originally trained by IIC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_ehealth_kd_pipeline_es_5.5.1_3.0_1731290752512.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_ehealth_kd_pipeline_es_5.5.1_3.0_1731290752512.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_spanish_wwm_cased_ehealth_kd_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_spanish_wwm_cased_ehealth_kd_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_ehealth_kd_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|409.5 MB| + +## References + +https://huggingface.co/IIC/bert-base-spanish-wwm-cased-ehealth_kd + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_ai4privacy_english_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_ai4privacy_english_en.md new file mode 100644 index 00000000000000..abda28dd87ce7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_ai4privacy_english_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_ai4privacy_english BertForTokenClassification from xXiaobuding +author: John Snow Labs +name: bert_base_uncased_ai4privacy_english +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ai4privacy_english` is a English model originally trained by xXiaobuding. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ai4privacy_english_en_5.5.1_3.0_1731285288447.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ai4privacy_english_en_5.5.1_3.0_1731285288447.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_base_uncased_ai4privacy_english","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_base_uncased_ai4privacy_english", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ai4privacy_english| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|407.5 MB| + +## References + +https://huggingface.co/xXiaobuding/bert-base-uncased_ai4privacy_en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_ai4privacy_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_ai4privacy_english_pipeline_en.md new file mode 100644 index 00000000000000..3f1af225a7e1d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_ai4privacy_english_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_ai4privacy_english_pipeline pipeline BertForTokenClassification from xXiaobuding +author: John Snow Labs +name: bert_base_uncased_ai4privacy_english_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ai4privacy_english_pipeline` is a English model originally trained by xXiaobuding. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ai4privacy_english_pipeline_en_5.5.1_3.0_1731285310338.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ai4privacy_english_pipeline_en_5.5.1_3.0_1731285310338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_ai4privacy_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_ai4privacy_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ai4privacy_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.5 MB| + +## References + +https://huggingface.co/xXiaobuding/bert-base-uncased_ai4privacy_en + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_emotion_prikshit7766_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_emotion_prikshit7766_en.md new file mode 100644 index 00000000000000..e53b97aac910c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_emotion_prikshit7766_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_emotion_prikshit7766 BertForSequenceClassification from Prikshit7766 +author: John Snow Labs +name: bert_base_uncased_emotion_prikshit7766 +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_prikshit7766` is a English model originally trained by Prikshit7766. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_prikshit7766_en_5.5.1_3.0_1731310162648.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_prikshit7766_en_5.5.1_3.0_1731310162648.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_base_uncased_emotion_prikshit7766","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_emotion_prikshit7766", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_prikshit7766| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Prikshit7766/bert-base-uncased-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_emotion_prikshit7766_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_emotion_prikshit7766_pipeline_en.md new file mode 100644 index 00000000000000..4a154aae33762a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_emotion_prikshit7766_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_emotion_prikshit7766_pipeline pipeline BertForSequenceClassification from Prikshit7766 +author: John Snow Labs +name: bert_base_uncased_emotion_prikshit7766_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_emotion_prikshit7766_pipeline` is a English model originally trained by Prikshit7766. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_prikshit7766_pipeline_en_5.5.1_3.0_1731310189528.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_prikshit7766_pipeline_en_5.5.1_3.0_1731310189528.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_emotion_prikshit7766_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_emotion_prikshit7766_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_prikshit7766_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Prikshit7766/bert-base-uncased-emotion + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_figurative_language_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_figurative_language_en.md new file mode 100644 index 00000000000000..13849f955bb2ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_figurative_language_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_base_uncased_figurative_language BertForQuestionAnswering from DunnBC22 +author: John Snow Labs +name: bert_base_uncased_figurative_language +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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_uncased_figurative_language` is a English model originally trained by DunnBC22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_figurative_language_en_5.5.1_3.0_1731308200930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_figurative_language_en_5.5.1_3.0_1731308200930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_figurative_language","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_figurative_language", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_figurative_language| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/DunnBC22/bert-base-uncased-Figurative_Language \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_figurative_language_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_figurative_language_pipeline_en.md new file mode 100644 index 00000000000000..1776fc9fe52fe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_figurative_language_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_base_uncased_figurative_language_pipeline pipeline BertForQuestionAnswering from DunnBC22 +author: John Snow Labs +name: bert_base_uncased_figurative_language_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_figurative_language_pipeline` is a English model originally trained by DunnBC22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_figurative_language_pipeline_en_5.5.1_3.0_1731308223519.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_figurative_language_pipeline_en_5.5.1_3.0_1731308223519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_figurative_language_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_figurative_language_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_figurative_language_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/DunnBC22/bert-base-uncased-Figurative_Language + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_finetuned_triviaqa_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_finetuned_triviaqa_en.md new file mode 100644 index 00000000000000..5d53f223d9f537 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_finetuned_triviaqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_triviaqa BertForQuestionAnswering from mirbostani +author: John Snow Labs +name: bert_base_uncased_finetuned_triviaqa +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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_uncased_finetuned_triviaqa` is a English model originally trained by mirbostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_triviaqa_en_5.5.1_3.0_1731308084796.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_triviaqa_en_5.5.1_3.0_1731308084796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_triviaqa","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_base_uncased_finetuned_triviaqa", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_triviaqa| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/mirbostani/bert-base-uncased-finetuned-triviaqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_finetuned_triviaqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_finetuned_triviaqa_pipeline_en.md new file mode 100644 index 00000000000000..df63c8a41e3860 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_finetuned_triviaqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_triviaqa_pipeline pipeline BertForQuestionAnswering from mirbostani +author: John Snow Labs +name: bert_base_uncased_finetuned_triviaqa_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_triviaqa_pipeline` is a English model originally trained by mirbostani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_triviaqa_pipeline_en_5.5.1_3.0_1731308106385.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_triviaqa_pipeline_en_5.5.1_3.0_1731308106385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_finetuned_triviaqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_finetuned_triviaqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_triviaqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/mirbostani/bert-base-uncased-finetuned-triviaqa + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_sba_clf_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_sba_clf_en.md new file mode 100644 index 00000000000000..cb245e60cadf96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_sba_clf_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_base_uncased_sba_clf BertForSequenceClassification from ahmedselhady +author: John Snow Labs +name: bert_base_uncased_sba_clf +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_sba_clf` is a English model originally trained by ahmedselhady. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sba_clf_en_5.5.1_3.0_1731309789010.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sba_clf_en_5.5.1_3.0_1731309789010.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_base_uncased_sba_clf","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sba_clf", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sba_clf| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ahmedselhady/bert-base-uncased-sba-clf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_sba_clf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_sba_clf_pipeline_en.md new file mode 100644 index 00000000000000..6091255e81402f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_base_uncased_sba_clf_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_base_uncased_sba_clf_pipeline pipeline BertForSequenceClassification from ahmedselhady +author: John Snow Labs +name: bert_base_uncased_sba_clf_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sba_clf_pipeline` is a English model originally trained by ahmedselhady. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sba_clf_pipeline_en_5.5.1_3.0_1731309811038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sba_clf_pipeline_en_5.5.1_3.0_1731309811038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_base_uncased_sba_clf_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_base_uncased_sba_clf_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sba_clf_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ahmedselhady/bert-base-uncased-sba-clf + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_classifier_spanish_news_classification_headlines_es.md b/docs/_posts/ahmedlone127/2024-11-11-bert_classifier_spanish_news_classification_headlines_es.md new file mode 100644 index 00000000000000..946e766f6b0406 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_classifier_spanish_news_classification_headlines_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish bert_classifier_spanish_news_classification_headlines BertForSequenceClassification from M47Labs +author: John Snow Labs +name: bert_classifier_spanish_news_classification_headlines +date: 2024-11-11 +tags: [es, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_spanish_news_classification_headlines` is a Castilian, Spanish model originally trained by M47Labs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_spanish_news_classification_headlines_es_5.5.1_3.0_1731309478600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_spanish_news_classification_headlines_es_5.5.1_3.0_1731309478600.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_classifier_spanish_news_classification_headlines","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_spanish_news_classification_headlines", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_spanish_news_classification_headlines| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/M47Labs/spanish_news_classification_headlines \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_classifier_spanish_news_classification_headlines_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-11-bert_classifier_spanish_news_classification_headlines_pipeline_es.md new file mode 100644 index 00000000000000..70a54f52790f47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_classifier_spanish_news_classification_headlines_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bert_classifier_spanish_news_classification_headlines_pipeline pipeline BertForSequenceClassification from M47Labs +author: John Snow Labs +name: bert_classifier_spanish_news_classification_headlines_pipeline +date: 2024-11-11 +tags: [es, open_source, pipeline, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_spanish_news_classification_headlines_pipeline` is a Castilian, Spanish model originally trained by M47Labs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_spanish_news_classification_headlines_pipeline_es_5.5.1_3.0_1731309503064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_spanish_news_classification_headlines_pipeline_es_5.5.1_3.0_1731309503064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_classifier_spanish_news_classification_headlines_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_classifier_spanish_news_classification_headlines_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_spanish_news_classification_headlines_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|411.8 MB| + +## References + +https://huggingface.co/M47Labs/spanish_news_classification_headlines + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_arcchialogy_ner_hp_tunned_hgf_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_arcchialogy_ner_hp_tunned_hgf_en.md new file mode 100644 index 00000000000000..945120133a1b34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_arcchialogy_ner_hp_tunned_hgf_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_arcchialogy_ner_hp_tunned_hgf BertForTokenClassification from nstrn-mo +author: John Snow Labs +name: bert_finetuned_arcchialogy_ner_hp_tunned_hgf +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_arcchialogy_ner_hp_tunned_hgf` is a English model originally trained by nstrn-mo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_arcchialogy_ner_hp_tunned_hgf_en_5.5.1_3.0_1731286093619.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_arcchialogy_ner_hp_tunned_hgf_en_5.5.1_3.0_1731286093619.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_arcchialogy_ner_hp_tunned_hgf","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_arcchialogy_ner_hp_tunned_hgf", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_arcchialogy_ner_hp_tunned_hgf| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/nstrn-mo/bert-finetuned-arcchialogy-ner-hp-tunned-hgf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline_en.md new file mode 100644 index 00000000000000..4cd4824a5257ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline pipeline BertForTokenClassification from nstrn-mo +author: John Snow Labs +name: bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline` is a English model originally trained by nstrn-mo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline_en_5.5.1_3.0_1731286113957.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline_en_5.5.1_3.0_1731286113957.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_arcchialogy_ner_hp_tunned_hgf_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/nstrn-mo/bert-finetuned-arcchialogy-ner-hp-tunned-hgf + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner4_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner4_en.md new file mode 100644 index 00000000000000..d489e3c0465fe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner4_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner4 BertForTokenClassification from kabear +author: John Snow Labs +name: bert_finetuned_ner4 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner4` is a English model originally trained by kabear. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner4_en_5.5.1_3.0_1731290275551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner4_en_5.5.1_3.0_1731290275551.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner4","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner4", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner4| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/kabear/bert-finetuned-ner4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner4_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner4_pipeline_en.md new file mode 100644 index 00000000000000..354524cbb23379 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner4_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner4_pipeline pipeline BertForTokenClassification from kabear +author: John Snow Labs +name: bert_finetuned_ner4_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner4_pipeline` is a English model originally trained by kabear. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner4_pipeline_en_5.5.1_3.0_1731290296627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner4_pipeline_en_5.5.1_3.0_1731290296627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner4_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner4_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner4_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/kabear/bert-finetuned-ner4 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_dylanalloy_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_dylanalloy_en.md new file mode 100644 index 00000000000000..79a4b816f47bd9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_dylanalloy_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner_dylanalloy BertForTokenClassification from dylanalloy +author: John Snow Labs +name: bert_finetuned_ner_dylanalloy +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_dylanalloy` is a English model originally trained by dylanalloy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_dylanalloy_en_5.5.1_3.0_1731290622914.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_dylanalloy_en_5.5.1_3.0_1731290622914.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_dylanalloy","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_dylanalloy", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_dylanalloy| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/dylanalloy/bert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_dylanalloy_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_dylanalloy_pipeline_en.md new file mode 100644 index 00000000000000..06d8a06ecb6c91 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_dylanalloy_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_dylanalloy_pipeline pipeline BertForTokenClassification from dylanalloy +author: John Snow Labs +name: bert_finetuned_ner_dylanalloy_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_dylanalloy_pipeline` is a English model originally trained by dylanalloy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_dylanalloy_pipeline_en_5.5.1_3.0_1731290643740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_dylanalloy_pipeline_en_5.5.1_3.0_1731290643740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_dylanalloy_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_dylanalloy_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_dylanalloy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/dylanalloy/bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_joshuaaax_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_joshuaaax_en.md new file mode 100644 index 00000000000000..25be0b2d8d6e46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_joshuaaax_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner_joshuaaax BertForTokenClassification from JoshuaAAX +author: John Snow Labs +name: bert_finetuned_ner_joshuaaax +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_joshuaaax` is a English model originally trained by JoshuaAAX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_joshuaaax_en_5.5.1_3.0_1731285567463.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_joshuaaax_en_5.5.1_3.0_1731285567463.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_joshuaaax","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_joshuaaax", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_joshuaaax| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/JoshuaAAX/bert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_joshuaaax_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_joshuaaax_pipeline_en.md new file mode 100644 index 00000000000000..dfa2e34b5b0404 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_joshuaaax_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_joshuaaax_pipeline pipeline BertForTokenClassification from JoshuaAAX +author: John Snow Labs +name: bert_finetuned_ner_joshuaaax_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_joshuaaax_pipeline` is a English model originally trained by JoshuaAAX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_joshuaaax_pipeline_en_5.5.1_3.0_1731285588723.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_joshuaaax_pipeline_en_5.5.1_3.0_1731285588723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_joshuaaax_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_joshuaaax_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_joshuaaax_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/JoshuaAAX/bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_nicodeb_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_nicodeb_en.md new file mode 100644 index 00000000000000..d03ee6a386a16b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_nicodeb_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner_nicodeb BertForTokenClassification from nicodeb +author: John Snow Labs +name: bert_finetuned_ner_nicodeb +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_nicodeb` is a English model originally trained by nicodeb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_nicodeb_en_5.5.1_3.0_1731285509207.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_nicodeb_en_5.5.1_3.0_1731285509207.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_nicodeb","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_nicodeb", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_nicodeb| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/nicodeb/bert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_nicodeb_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_nicodeb_pipeline_en.md new file mode 100644 index 00000000000000..4a314a016fde66 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_nicodeb_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_nicodeb_pipeline pipeline BertForTokenClassification from nicodeb +author: John Snow Labs +name: bert_finetuned_ner_nicodeb_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_nicodeb_pipeline` is a English model originally trained by nicodeb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_nicodeb_pipeline_en_5.5.1_3.0_1731285532547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_nicodeb_pipeline_en_5.5.1_3.0_1731285532547.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_nicodeb_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_nicodeb_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_nicodeb_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/nicodeb/bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_savoxism_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_savoxism_en.md new file mode 100644 index 00000000000000..7fde38c647fb3e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_savoxism_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner_savoxism BertForTokenClassification from Savoxism +author: John Snow Labs +name: bert_finetuned_ner_savoxism +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_savoxism` is a English model originally trained by Savoxism. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_savoxism_en_5.5.1_3.0_1731285227266.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_savoxism_en_5.5.1_3.0_1731285227266.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_savoxism","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_savoxism", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_savoxism| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/Savoxism/bert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_savoxism_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_savoxism_pipeline_en.md new file mode 100644 index 00000000000000..f14162b22365e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_savoxism_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_savoxism_pipeline pipeline BertForTokenClassification from Savoxism +author: John Snow Labs +name: bert_finetuned_ner_savoxism_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_savoxism_pipeline` is a English model originally trained by Savoxism. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_savoxism_pipeline_en_5.5.1_3.0_1731285251578.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_savoxism_pipeline_en_5.5.1_3.0_1731285251578.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_savoxism_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_savoxism_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_savoxism_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/Savoxism/bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_tornqvistmax_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_tornqvistmax_en.md new file mode 100644 index 00000000000000..9e8a3506c48127 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_tornqvistmax_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner_tornqvistmax BertForTokenClassification from tornqvistmax +author: John Snow Labs +name: bert_finetuned_ner_tornqvistmax +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_tornqvistmax` is a English model originally trained by tornqvistmax. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_tornqvistmax_en_5.5.1_3.0_1731290123499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_tornqvistmax_en_5.5.1_3.0_1731290123499.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_tornqvistmax","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_tornqvistmax", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_tornqvistmax| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/tornqvistmax/bert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_tornqvistmax_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_tornqvistmax_pipeline_en.md new file mode 100644 index 00000000000000..4ea57ab9740a0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_tornqvistmax_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_tornqvistmax_pipeline pipeline BertForTokenClassification from tornqvistmax +author: John Snow Labs +name: bert_finetuned_ner_tornqvistmax_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_tornqvistmax_pipeline` is a English model originally trained by tornqvistmax. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_tornqvistmax_pipeline_en_5.5.1_3.0_1731290144174.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_tornqvistmax_pipeline_en_5.5.1_3.0_1731290144174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_tornqvistmax_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_tornqvistmax_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_tornqvistmax_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.8 MB| + +## References + +https://huggingface.co/tornqvistmax/bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_viktoryes_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_viktoryes_en.md new file mode 100644 index 00000000000000..76e27e111f99aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_viktoryes_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_ner_viktoryes BertForTokenClassification from viktoryes +author: John Snow Labs +name: bert_finetuned_ner_viktoryes +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_viktoryes` is a English model originally trained by viktoryes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_viktoryes_en_5.5.1_3.0_1731299620506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_viktoryes_en_5.5.1_3.0_1731299620506.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_viktoryes","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_ner_viktoryes", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_viktoryes| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/viktoryes/bert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_viktoryes_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_viktoryes_pipeline_en.md new file mode 100644 index 00000000000000..e0e37af8b14502 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_ner_viktoryes_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_ner_viktoryes_pipeline pipeline BertForTokenClassification from viktoryes +author: John Snow Labs +name: bert_finetuned_ner_viktoryes_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_ner_viktoryes_pipeline` is a English model originally trained by viktoryes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_viktoryes_pipeline_en_5.5.1_3.0_1731299640955.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_ner_viktoryes_pipeline_en_5.5.1_3.0_1731299640955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_ner_viktoryes_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_ner_viktoryes_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_ner_viktoryes_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/viktoryes/bert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_semantic_augmentation_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_semantic_augmentation_ner_en.md new file mode 100644 index 00000000000000..7577ae96ee1838 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_semantic_augmentation_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_semantic_augmentation_ner RoBertaForTokenClassification from lsoni +author: John Snow Labs +name: bert_finetuned_semantic_augmentation_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_semantic_augmentation_ner` is a English model originally trained by lsoni. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_semantic_augmentation_ner_en_5.5.1_3.0_1731314256488.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_semantic_augmentation_ner_en_5.5.1_3.0_1731314256488.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("bert_finetuned_semantic_augmentation_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("bert_finetuned_semantic_augmentation_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_semantic_augmentation_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|439.3 MB| + +## References + +https://huggingface.co/lsoni/bert-finetuned-semantic-augmentation-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_accelerate_3_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_accelerate_3_en.md new file mode 100644 index 00000000000000..d48a730c987b85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_accelerate_3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_finetuned_squad_accelerate_3 BertForQuestionAnswering from camilag +author: John Snow Labs +name: bert_finetuned_squad_accelerate_3 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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_finetuned_squad_accelerate_3` is a English model originally trained by camilag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_3_en_5.5.1_3.0_1731307814641.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_3_en_5.5.1_3.0_1731307814641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_accelerate_3","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_accelerate_3", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_squad_accelerate_3| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/camilag/bert-finetuned-squad-accelerate-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_accelerate_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_accelerate_3_pipeline_en.md new file mode 100644 index 00000000000000..68c9155a6c626c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_accelerate_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_finetuned_squad_accelerate_3_pipeline pipeline BertForQuestionAnswering from camilag +author: John Snow Labs +name: bert_finetuned_squad_accelerate_3_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_accelerate_3_pipeline` is a English model originally trained by camilag. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_3_pipeline_en_5.5.1_3.0_1731307835513.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_accelerate_3_pipeline_en_5.5.1_3.0_1731307835513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_squad_accelerate_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_squad_accelerate_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_squad_accelerate_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/camilag/bert-finetuned-squad-accelerate-3 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_dokyoungkim_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_dokyoungkim_en.md new file mode 100644 index 00000000000000..d679abf825b127 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_dokyoungkim_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_finetuned_squad_dokyoungkim BertForQuestionAnswering from dokyoungkim +author: John Snow Labs +name: bert_finetuned_squad_dokyoungkim +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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_finetuned_squad_dokyoungkim` is a English model originally trained by dokyoungkim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_dokyoungkim_en_5.5.1_3.0_1731307566830.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_dokyoungkim_en_5.5.1_3.0_1731307566830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_dokyoungkim","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_finetuned_squad_dokyoungkim", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_squad_dokyoungkim| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/dokyoungkim/bert-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_dokyoungkim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_dokyoungkim_pipeline_en.md new file mode 100644 index 00000000000000..5b98fabd4bac67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_squad_dokyoungkim_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_finetuned_squad_dokyoungkim_pipeline pipeline BertForQuestionAnswering from dokyoungkim +author: John Snow Labs +name: bert_finetuned_squad_dokyoungkim_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_squad_dokyoungkim_pipeline` is a English model originally trained by dokyoungkim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_dokyoungkim_pipeline_en_5.5.1_3.0_1731307587294.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_squad_dokyoungkim_pipeline_en_5.5.1_3.0_1731307587294.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_squad_dokyoungkim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_squad_dokyoungkim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_squad_dokyoungkim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/dokyoungkim/bert-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_tmvar_corpus_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_tmvar_corpus_en.md new file mode 100644 index 00000000000000..fcfce703b9dd61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_tmvar_corpus_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_finetuned_tmvar_corpus BertForTokenClassification from Salvatore +author: John Snow Labs +name: bert_finetuned_tmvar_corpus +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_tmvar_corpus` is a English model originally trained by Salvatore. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_tmvar_corpus_en_5.5.1_3.0_1731298905916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_tmvar_corpus_en_5.5.1_3.0_1731298905916.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_tmvar_corpus","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_finetuned_tmvar_corpus", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_tmvar_corpus| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|362.8 MB| + +## References + +https://huggingface.co/Salvatore/bert-finetuned-tmvar-corpus \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_tmvar_corpus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_tmvar_corpus_pipeline_en.md new file mode 100644 index 00000000000000..2fbce5d2dc7d67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_finetuned_tmvar_corpus_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_finetuned_tmvar_corpus_pipeline pipeline BertForTokenClassification from Salvatore +author: John Snow Labs +name: bert_finetuned_tmvar_corpus_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_tmvar_corpus_pipeline` is a English model originally trained by Salvatore. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_tmvar_corpus_pipeline_en_5.5.1_3.0_1731298925116.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_tmvar_corpus_pipeline_en_5.5.1_3.0_1731298925116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_finetuned_tmvar_corpus_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_finetuned_tmvar_corpus_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_tmvar_corpus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|362.9 MB| + +## References + +https://huggingface.co/Salvatore/bert-finetuned-tmvar-corpus + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_large_finetuned_phishing_junginkim_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_large_finetuned_phishing_junginkim_en.md new file mode 100644 index 00000000000000..6c840df7ee5583 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_large_finetuned_phishing_junginkim_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_large_finetuned_phishing_junginkim BertForSequenceClassification from Junginkim +author: John Snow Labs +name: bert_large_finetuned_phishing_junginkim +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_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_finetuned_phishing_junginkim` is a English model originally trained by Junginkim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_junginkim_en_5.5.1_3.0_1731310431818.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_junginkim_en_5.5.1_3.0_1731310431818.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_large_finetuned_phishing_junginkim","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_finetuned_phishing_junginkim", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_finetuned_phishing_junginkim| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Junginkim/bert-large-finetuned-phishing \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_large_finetuned_phishing_junginkim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_large_finetuned_phishing_junginkim_pipeline_en.md new file mode 100644 index 00000000000000..dbfb6eb102677c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_large_finetuned_phishing_junginkim_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_large_finetuned_phishing_junginkim_pipeline pipeline BertForSequenceClassification from Junginkim +author: John Snow Labs +name: bert_large_finetuned_phishing_junginkim_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_finetuned_phishing_junginkim_pipeline` is a English model originally trained by Junginkim. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_junginkim_pipeline_en_5.5.1_3.0_1731310494277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_finetuned_phishing_junginkim_pipeline_en_5.5.1_3.0_1731310494277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_finetuned_phishing_junginkim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_finetuned_phishing_junginkim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_finetuned_phishing_junginkim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Junginkim/bert-large-finetuned-phishing + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_en.md new file mode 100644 index 00000000000000..c50d06093bd5f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_large_uncased_whole_word_masking_finetuned_squad_dev_i BertForQuestionAnswering from mdzrg +author: John Snow Labs +name: bert_large_uncased_whole_word_masking_finetuned_squad_dev_i +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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_large_uncased_whole_word_masking_finetuned_squad_dev_i` is a English model originally trained by mdzrg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_en_5.5.1_3.0_1731307616981.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_dev_i_en_5.5.1_3.0_1731307616981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_finetuned_squad_dev_i","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_large_uncased_whole_word_masking_finetuned_squad_dev_i", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_whole_word_masking_finetuned_squad_dev_i| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/mdzrg/bert-large-uncased-whole-word-masking-finetuned-squad-dev-I \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline_en.md new file mode 100644 index 00000000000000..b1d311833b4854 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline pipeline BertForQuestionAnswering from mdzrg +author: John Snow Labs +name: bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline` is a English model originally trained by mdzrg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline_en_5.5.1_3.0_1731307680614.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_dev_i_pipeline_en_5.5.1_3.0_1731307680614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_whole_word_masking_finetuned_squad_dev_i_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/mdzrg/bert-large-uncased-whole-word-masking-finetuned-squad-dev-I + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_model_news_aggregator_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_model_news_aggregator_en.md new file mode 100644 index 00000000000000..1ed2337d2ed860 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_model_news_aggregator_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_model_news_aggregator BertForSequenceClassification from Subash2580 +author: John Snow Labs +name: bert_model_news_aggregator +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_model_news_aggregator` is a English model originally trained by Subash2580. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_model_news_aggregator_en_5.5.1_3.0_1731309957668.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_model_news_aggregator_en_5.5.1_3.0_1731309957668.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_model_news_aggregator","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_model_news_aggregator", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_model_news_aggregator| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Subash2580/Bert_model_news_aggregator \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_model_news_aggregator_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_model_news_aggregator_pipeline_en.md new file mode 100644 index 00000000000000..3e701d5cd4a867 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_model_news_aggregator_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_model_news_aggregator_pipeline pipeline BertForSequenceClassification from Subash2580 +author: John Snow Labs +name: bert_model_news_aggregator_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_model_news_aggregator_pipeline` is a English model originally trained by Subash2580. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_model_news_aggregator_pipeline_en_5.5.1_3.0_1731309980168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_model_news_aggregator_pipeline_en_5.5.1_3.0_1731309980168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_model_news_aggregator_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_model_news_aggregator_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_model_news_aggregator_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Subash2580/Bert_model_news_aggregator + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_news_class_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_news_class_en.md new file mode 100644 index 00000000000000..6cfc866d5d272d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_news_class_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bert_news_class BertForSequenceClassification from cssupport +author: John Snow Labs +name: bert_news_class +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_news_class` is a English model originally trained by cssupport. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_news_class_en_5.5.1_3.0_1731310012331.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_news_class_en_5.5.1_3.0_1731310012331.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_news_class","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_news_class", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_news_class| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/cssupport/bert-news-class \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_news_class_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_news_class_pipeline_en.md new file mode 100644 index 00000000000000..a5319d61f401dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_news_class_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bert_news_class_pipeline pipeline BertForSequenceClassification from cssupport +author: John Snow Labs +name: bert_news_class_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_news_class_pipeline` is a English model originally trained by cssupport. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_news_class_pipeline_en_5.5.1_3.0_1731310049127.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_news_class_pipeline_en_5.5.1_3.0_1731310049127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_news_class_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_news_class_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_news_class_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/cssupport/bert-news-class + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_portuguese_squad2_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_portuguese_squad2_en.md new file mode 100644 index 00000000000000..5792d6c2ed183a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_portuguese_squad2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_portuguese_squad2 BertForQuestionAnswering from lfcc +author: John Snow Labs +name: bert_portuguese_squad2 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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_portuguese_squad2` is a English model originally trained by lfcc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_portuguese_squad2_en_5.5.1_3.0_1731289735794.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_portuguese_squad2_en_5.5.1_3.0_1731289735794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_portuguese_squad2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_portuguese_squad2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_portuguese_squad2| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/lfcc/bert-portuguese-squad2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_portuguese_squad2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_portuguese_squad2_pipeline_en.md new file mode 100644 index 00000000000000..626a4567ed3c3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_portuguese_squad2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_portuguese_squad2_pipeline pipeline BertForQuestionAnswering from lfcc +author: John Snow Labs +name: bert_portuguese_squad2_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_portuguese_squad2_pipeline` is a English model originally trained by lfcc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_portuguese_squad2_pipeline_en_5.5.1_3.0_1731289756826.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_portuguese_squad2_pipeline_en_5.5.1_3.0_1731289756826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_portuguese_squad2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_portuguese_squad2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_portuguese_squad2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/lfcc/bert-portuguese-squad2 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_sliding_window_epoch_3_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_sliding_window_epoch_3_en.md new file mode 100644 index 00000000000000..cc75237af2e796 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_sliding_window_epoch_3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English bert_sliding_window_epoch_3 BertForQuestionAnswering from Whalejay +author: John Snow Labs +name: bert_sliding_window_epoch_3 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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_sliding_window_epoch_3` is a English model originally trained by Whalejay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sliding_window_epoch_3_en_5.5.1_3.0_1731307867943.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sliding_window_epoch_3_en_5.5.1_3.0_1731307867943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("bert_sliding_window_epoch_3","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("bert_sliding_window_epoch_3", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sliding_window_epoch_3| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Whalejay/bert-sliding-window_epoch_3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_sliding_window_epoch_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bert_sliding_window_epoch_3_pipeline_en.md new file mode 100644 index 00000000000000..2edab514beaa3a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_sliding_window_epoch_3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bert_sliding_window_epoch_3_pipeline pipeline BertForQuestionAnswering from Whalejay +author: John Snow Labs +name: bert_sliding_window_epoch_3_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sliding_window_epoch_3_pipeline` is a English model originally trained by Whalejay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sliding_window_epoch_3_pipeline_en_5.5.1_3.0_1731307932813.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sliding_window_epoch_3_pipeline_en_5.5.1_3.0_1731307932813.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_sliding_window_epoch_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_sliding_window_epoch_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sliding_window_epoch_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Whalejay/bert-sliding-window_epoch_3 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_xomlac_ner_pipeline_zh.md b/docs/_posts/ahmedlone127/2024-11-11-bert_xomlac_ner_pipeline_zh.md new file mode 100644 index 00000000000000..2122b09d6699e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_xomlac_ner_pipeline_zh.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Chinese bert_xomlac_ner_pipeline pipeline BertForTokenClassification from b3x0m +author: John Snow Labs +name: bert_xomlac_ner_pipeline +date: 2024-11-11 +tags: [zh, open_source, pipeline, onnx] +task: Named Entity Recognition +language: zh +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_xomlac_ner_pipeline` is a Chinese model originally trained by b3x0m. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_xomlac_ner_pipeline_zh_5.5.1_3.0_1731298814714.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_xomlac_ner_pipeline_zh_5.5.1_3.0_1731298814714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bert_xomlac_ner_pipeline", lang = "zh") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bert_xomlac_ner_pipeline", lang = "zh") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_xomlac_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|381.1 MB| + +## References + +https://huggingface.co/b3x0m/bert-xomlac-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bert_xomlac_ner_zh.md b/docs/_posts/ahmedlone127/2024-11-11-bert_xomlac_ner_zh.md new file mode 100644 index 00000000000000..8cfbfeb70a61e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bert_xomlac_ner_zh.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Chinese bert_xomlac_ner BertForTokenClassification from b3x0m +author: John Snow Labs +name: bert_xomlac_ner +date: 2024-11-11 +tags: [zh, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: zh +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_xomlac_ner` is a Chinese model originally trained by b3x0m. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_xomlac_ner_zh_5.5.1_3.0_1731298794255.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_xomlac_ner_zh_5.5.1_3.0_1731298794255.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') + +tokenClassifier = BertForTokenClassification.pretrained("bert_xomlac_ner","zh") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("bert_xomlac_ner", "zh") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_xomlac_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|zh| +|Size:|381.1 MB| + +## References + +https://huggingface.co/b3x0m/bert-xomlac-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_13_en.md b/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_13_en.md new file mode 100644 index 00000000000000..9302d0b8eb13ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_13_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English beto_finetuned_ner_13 BertForTokenClassification from ifis +author: John Snow Labs +name: beto_finetuned_ner_13 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner_13` is a English model originally trained by ifis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_13_en_5.5.1_3.0_1731291039879.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_13_en_5.5.1_3.0_1731291039879.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') + +tokenClassifier = BertForTokenClassification.pretrained("beto_finetuned_ner_13","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("beto_finetuned_ner_13", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|beto_finetuned_ner_13| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/ifis/BETO-finetuned-ner-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_13_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_13_pipeline_en.md new file mode 100644 index 00000000000000..204268321dad36 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_13_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English beto_finetuned_ner_13_pipeline pipeline BertForTokenClassification from ifis +author: John Snow Labs +name: beto_finetuned_ner_13_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner_13_pipeline` is a English model originally trained by ifis. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_13_pipeline_en_5.5.1_3.0_1731291060919.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_13_pipeline_en_5.5.1_3.0_1731291060919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("beto_finetuned_ner_13_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("beto_finetuned_ner_13_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|beto_finetuned_ner_13_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/ifis/BETO-finetuned-ner-13 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_en.md new file mode 100644 index 00000000000000..ac6e503632a509 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English beto_finetuned_ner BertForTokenClassification from JoshuaAAX +author: John Snow Labs +name: beto_finetuned_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner` is a English model originally trained by JoshuaAAX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_en_5.5.1_3.0_1731291099811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_en_5.5.1_3.0_1731291099811.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') + +tokenClassifier = BertForTokenClassification.pretrained("beto_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("beto_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|beto_finetuned_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/JoshuaAAX/beto-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..0f310238b10ee7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-beto_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English beto_finetuned_ner_pipeline pipeline BertForTokenClassification from JoshuaAAX +author: John Snow Labs +name: beto_finetuned_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_finetuned_ner_pipeline` is a English model originally trained by JoshuaAAX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_pipeline_en_5.5.1_3.0_1731291120382.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_finetuned_ner_pipeline_en_5.5.1_3.0_1731291120382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("beto_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("beto_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|beto_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/JoshuaAAX/beto-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-beto_sayula_popoluca_en.md b/docs/_posts/ahmedlone127/2024-11-11-beto_sayula_popoluca_en.md new file mode 100644 index 00000000000000..5779fb8f6fdf0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-beto_sayula_popoluca_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English beto_sayula_popoluca BertForTokenClassification from hugo-albert +author: John Snow Labs +name: beto_sayula_popoluca +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_sayula_popoluca` is a English model originally trained by hugo-albert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_sayula_popoluca_en_5.5.1_3.0_1731290885885.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_sayula_popoluca_en_5.5.1_3.0_1731290885885.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') + +tokenClassifier = BertForTokenClassification.pretrained("beto_sayula_popoluca","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("beto_sayula_popoluca", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|beto_sayula_popoluca| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/hugo-albert/beto-pos \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-beto_sayula_popoluca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-beto_sayula_popoluca_pipeline_en.md new file mode 100644 index 00000000000000..41a5e1a08577a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-beto_sayula_popoluca_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English beto_sayula_popoluca_pipeline pipeline BertForTokenClassification from hugo-albert +author: John Snow Labs +name: beto_sayula_popoluca_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_sayula_popoluca_pipeline` is a English model originally trained by hugo-albert. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_sayula_popoluca_pipeline_en_5.5.1_3.0_1731290909568.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_sayula_popoluca_pipeline_en_5.5.1_3.0_1731290909568.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("beto_sayula_popoluca_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("beto_sayula_popoluca_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|beto_sayula_popoluca_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.7 MB| + +## References + +https://huggingface.co/hugo-albert/beto-pos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-beto_sentiment_analysis_finetuned_en.md b/docs/_posts/ahmedlone127/2024-11-11-beto_sentiment_analysis_finetuned_en.md new file mode 100644 index 00000000000000..4272f17101d73e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-beto_sentiment_analysis_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English beto_sentiment_analysis_finetuned BertForSequenceClassification from stinoco +author: John Snow Labs +name: beto_sentiment_analysis_finetuned +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_sentiment_analysis_finetuned` is a English model originally trained by stinoco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_sentiment_analysis_finetuned_en_5.5.1_3.0_1731309155278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_sentiment_analysis_finetuned_en_5.5.1_3.0_1731309155278.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("beto_sentiment_analysis_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("beto_sentiment_analysis_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|beto_sentiment_analysis_finetuned| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.3 MB| + +## References + +https://huggingface.co/stinoco/beto-sentiment-analysis-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-beto_sentiment_analysis_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-beto_sentiment_analysis_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..b4e527ace7b1f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-beto_sentiment_analysis_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English beto_sentiment_analysis_finetuned_pipeline pipeline BertForSequenceClassification from stinoco +author: John Snow Labs +name: beto_sentiment_analysis_finetuned_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`beto_sentiment_analysis_finetuned_pipeline` is a English model originally trained by stinoco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/beto_sentiment_analysis_finetuned_pipeline_en_5.5.1_3.0_1731309178136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/beto_sentiment_analysis_finetuned_pipeline_en_5.5.1_3.0_1731309178136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("beto_sentiment_analysis_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("beto_sentiment_analysis_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|beto_sentiment_analysis_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|411.4 MB| + +## References + +https://huggingface.co/stinoco/beto-sentiment-analysis-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_99gpt_v1_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_99gpt_v1_en.md new file mode 100644 index 00000000000000..6fe0fe3ea4658e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_99gpt_v1_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_99gpt_v1 BGEEmbeddings from marroyo777 +author: John Snow Labs +name: bge_99gpt_v1 +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_99gpt_v1` is a English model originally trained by marroyo777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_99gpt_v1_en_5.5.1_3.0_1731313056005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_99gpt_v1_en_5.5.1_3.0_1731313056005.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") + +embeddings = BGEEmbeddings.pretrained("bge_99gpt_v1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_99gpt_v1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_99gpt_v1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|116.0 MB| + +## References + +https://huggingface.co/marroyo777/bge-99GPT-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_99gpt_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_99gpt_v1_pipeline_en.md new file mode 100644 index 00000000000000..1acf893dba9fe5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_99gpt_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_99gpt_v1_pipeline pipeline BGEEmbeddings from marroyo777 +author: John Snow Labs +name: bge_99gpt_v1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_99gpt_v1_pipeline` is a English model originally trained by marroyo777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_99gpt_v1_pipeline_en_5.5.1_3.0_1731313065265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_99gpt_v1_pipeline_en_5.5.1_3.0_1731313065265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_99gpt_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_99gpt_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_99gpt_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|116.0 MB| + +## References + +https://huggingface.co/marroyo777/bge-99GPT-v1 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_course_recommender_v2_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_course_recommender_v2_en.md new file mode 100644 index 00000000000000..af03cfe01992b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_course_recommender_v2_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_english_v1_5_course_recommender_v2 BGEEmbeddings from datasocietyco +author: John Snow Labs +name: bge_base_english_v1_5_course_recommender_v2 +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_course_recommender_v2` is a English model originally trained by datasocietyco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v2_en_5.5.1_3.0_1731313437646.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v2_en_5.5.1_3.0_1731313437646.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") + +embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_course_recommender_v2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_english_v1_5_course_recommender_v2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_course_recommender_v2| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|375.2 MB| + +## References + +https://huggingface.co/datasocietyco/bge-base-en-v1.5-course-recommender-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_course_recommender_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_course_recommender_v2_pipeline_en.md new file mode 100644 index 00000000000000..512787f72c67f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_course_recommender_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_course_recommender_v2_pipeline pipeline BGEEmbeddings from datasocietyco +author: John Snow Labs +name: bge_base_english_v1_5_course_recommender_v2_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_course_recommender_v2_pipeline` is a English model originally trained by datasocietyco. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v2_pipeline_en_5.5.1_3.0_1731313469876.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_course_recommender_v2_pipeline_en_5.5.1_3.0_1731313469876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_course_recommender_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_course_recommender_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_course_recommender_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|375.2 MB| + +## References + +https://huggingface.co/datasocietyco/bge-base-en-v1.5-course-recommender-v2 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_finetuned_osllmai_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_finetuned_osllmai_v1_pipeline_en.md new file mode 100644 index 00000000000000..c18f2e8cbf2336 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_base_english_v1_5_finetuned_osllmai_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_english_v1_5_finetuned_osllmai_v1_pipeline pipeline BGEEmbeddings from osllmai +author: John Snow Labs +name: bge_base_english_v1_5_finetuned_osllmai_v1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_english_v1_5_finetuned_osllmai_v1_pipeline` is a English model originally trained by osllmai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_osllmai_v1_pipeline_en_5.5.1_3.0_1731313060461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_english_v1_5_finetuned_osllmai_v1_pipeline_en_5.5.1_3.0_1731313060461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_english_v1_5_finetuned_osllmai_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_english_v1_5_finetuned_osllmai_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_english_v1_5_finetuned_osllmai_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|404.3 MB| + +## References + +https://huggingface.co/osllmai/bge-base-en-v1.5-finetuned_osllmai_v1 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_base_legal_matryoshka_v1_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_base_legal_matryoshka_v1_en.md new file mode 100644 index 00000000000000..9647d613397e49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_base_legal_matryoshka_v1_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_base_legal_matryoshka_v1 BGEEmbeddings from Tejasw1 +author: John Snow Labs +name: bge_base_legal_matryoshka_v1 +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_legal_matryoshka_v1` is a English model originally trained by Tejasw1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_legal_matryoshka_v1_en_5.5.1_3.0_1731312723474.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_legal_matryoshka_v1_en_5.5.1_3.0_1731312723474.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") + +embeddings = BGEEmbeddings.pretrained("bge_base_legal_matryoshka_v1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_base_legal_matryoshka_v1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_legal_matryoshka_v1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|383.6 MB| + +## References + +https://huggingface.co/Tejasw1/bge-base-legal-matryoshka-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_base_legal_matryoshka_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_base_legal_matryoshka_v1_pipeline_en.md new file mode 100644 index 00000000000000..c30db01371301c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_base_legal_matryoshka_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_base_legal_matryoshka_v1_pipeline pipeline BGEEmbeddings from Tejasw1 +author: John Snow Labs +name: bge_base_legal_matryoshka_v1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_base_legal_matryoshka_v1_pipeline` is a English model originally trained by Tejasw1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_base_legal_matryoshka_v1_pipeline_en_5.5.1_3.0_1731312753524.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_base_legal_matryoshka_v1_pipeline_en_5.5.1_3.0_1731312753524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_base_legal_matryoshka_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_base_legal_matryoshka_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_base_legal_matryoshka_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|383.6 MB| + +## References + +https://huggingface.co/Tejasw1/bge-base-legal-matryoshka-v1 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_large_zhtw_v1_5_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_large_zhtw_v1_5_en.md new file mode 100644 index 00000000000000..cd14d7182a0705 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_large_zhtw_v1_5_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_large_zhtw_v1_5 BGEEmbeddings from cfchu +author: John Snow Labs +name: bge_large_zhtw_v1_5 +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_zhtw_v1_5` is a English model originally trained by cfchu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_zhtw_v1_5_en_5.5.1_3.0_1731312857829.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_zhtw_v1_5_en_5.5.1_3.0_1731312857829.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") + +embeddings = BGEEmbeddings.pretrained("bge_large_zhtw_v1_5","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_large_zhtw_v1_5","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_zhtw_v1_5| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/cfchu/bge-large-zhtw-v1.5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_large_zhtw_v1_5_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_large_zhtw_v1_5_pipeline_en.md new file mode 100644 index 00000000000000..7f7668a4d0feac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_large_zhtw_v1_5_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_large_zhtw_v1_5_pipeline pipeline BGEEmbeddings from cfchu +author: John Snow Labs +name: bge_large_zhtw_v1_5_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_large_zhtw_v1_5_pipeline` is a English model originally trained by cfchu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_large_zhtw_v1_5_pipeline_en_5.5.1_3.0_1731312930680.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_large_zhtw_v1_5_pipeline_en_5.5.1_3.0_1731312930680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_large_zhtw_v1_5_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_large_zhtw_v1_5_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_large_zhtw_v1_5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/cfchu/bge-large-zhtw-v1.5 + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_micro_smiles_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_micro_smiles_en.md new file mode 100644 index 00000000000000..7ab539b2d3c30c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_micro_smiles_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_micro_smiles BGEEmbeddings from fpc +author: John Snow Labs +name: bge_micro_smiles +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_micro_smiles` is a English model originally trained by fpc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_micro_smiles_en_5.5.1_3.0_1731313171405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_micro_smiles_en_5.5.1_3.0_1731313171405.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") + +embeddings = BGEEmbeddings.pretrained("bge_micro_smiles","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_micro_smiles","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_micro_smiles| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|52.2 MB| + +## References + +https://huggingface.co/fpc/bge-micro-smiles \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_micro_smiles_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_micro_smiles_pipeline_en.md new file mode 100644 index 00000000000000..756aa54cbd12b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_micro_smiles_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_micro_smiles_pipeline pipeline BGEEmbeddings from fpc +author: John Snow Labs +name: bge_micro_smiles_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_micro_smiles_pipeline` is a English model originally trained by fpc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_micro_smiles_pipeline_en_5.5.1_3.0_1731313179313.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_micro_smiles_pipeline_en_5.5.1_3.0_1731313179313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_micro_smiles_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_micro_smiles_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_micro_smiles_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|52.2 MB| + +## References + +https://huggingface.co/fpc/bge-micro-smiles + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_ft_orc_0930_dates_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_ft_orc_0930_dates_en.md new file mode 100644 index 00000000000000..3d06606c8eb28e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_ft_orc_0930_dates_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_english_v1_5_ft_orc_0930_dates BGEEmbeddings from magnifi +author: John Snow Labs +name: bge_small_english_v1_5_ft_orc_0930_dates +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_ft_orc_0930_dates` is a English model originally trained by magnifi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0930_dates_en_5.5.1_3.0_1731312897567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0930_dates_en_5.5.1_3.0_1731312897567.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") + +embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_ft_orc_0930_dates","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_ft_orc_0930_dates","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_v1_5_ft_orc_0930_dates| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|110.3 MB| + +## References + +https://huggingface.co/magnifi/bge-small-en-v1.5-ft-orc-0930-dates \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_ft_orc_0930_dates_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_ft_orc_0930_dates_pipeline_en.md new file mode 100644 index 00000000000000..3000196ba709a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_ft_orc_0930_dates_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_small_english_v1_5_ft_orc_0930_dates_pipeline pipeline BGEEmbeddings from magnifi +author: John Snow Labs +name: bge_small_english_v1_5_ft_orc_0930_dates_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_ft_orc_0930_dates_pipeline` is a English model originally trained by magnifi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0930_dates_pipeline_en_5.5.1_3.0_1731312908553.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_ft_orc_0930_dates_pipeline_en_5.5.1_3.0_1731312908553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_small_english_v1_5_ft_orc_0930_dates_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_small_english_v1_5_ft_orc_0930_dates_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_v1_5_ft_orc_0930_dates_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|110.3 MB| + +## References + +https://huggingface.co/magnifi/bge-small-en-v1.5-ft-orc-0930-dates + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_rirag_obliqa_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_rirag_obliqa_en.md new file mode 100644 index 00000000000000..5ab25ba41147f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_small_english_v1_5_rirag_obliqa_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_small_english_v1_5_rirag_obliqa BGEEmbeddings from raul-delarosa99 +author: John Snow Labs +name: bge_small_english_v1_5_rirag_obliqa +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_small_english_v1_5_rirag_obliqa` is a English model originally trained by raul-delarosa99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_rirag_obliqa_en_5.5.1_3.0_1731313044537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_small_english_v1_5_rirag_obliqa_en_5.5.1_3.0_1731313044537.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") + +embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_rirag_obliqa","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_small_english_v1_5_rirag_obliqa","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_small_english_v1_5_rirag_obliqa| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|79.7 MB| + +## References + +https://huggingface.co/raul-delarosa99/bge-small-en-v1.5-RIRAG_ObliQA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_tuned_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_tuned_en.md new file mode 100644 index 00000000000000..555047dcb4072e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_tuned_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English bge_tuned BGEEmbeddings from minh132 +author: John Snow Labs +name: bge_tuned +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_tuned` is a English model originally trained by minh132. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_tuned_en_5.5.1_3.0_1731313341106.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_tuned_en_5.5.1_3.0_1731313341106.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") + +embeddings = BGEEmbeddings.pretrained("bge_tuned","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("bge_tuned","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_tuned| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/minh132/bge-tuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bge_tuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bge_tuned_pipeline_en.md new file mode 100644 index 00000000000000..6c8b87738cf009 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bge_tuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English bge_tuned_pipeline pipeline BGEEmbeddings from minh132 +author: John Snow Labs +name: bge_tuned_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bge_tuned_pipeline` is a English model originally trained by minh132. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bge_tuned_pipeline_en_5.5.1_3.0_1731313405235.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bge_tuned_pipeline_en_5.5.1_3.0_1731313405235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bge_tuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bge_tuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bge_tuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/minh132/bge-tuned + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bio_clinicalbert_medical_en.md b/docs/_posts/ahmedlone127/2024-11-11-bio_clinicalbert_medical_en.md new file mode 100644 index 00000000000000..58fbf151de55d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bio_clinicalbert_medical_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English bio_clinicalbert_medical BertForSequenceClassification from tarasophia +author: John Snow Labs +name: bio_clinicalbert_medical +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bio_clinicalbert_medical` is a English model originally trained by tarasophia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_medical_en_5.5.1_3.0_1731310240544.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_medical_en_5.5.1_3.0_1731310240544.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("bio_clinicalbert_medical","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bio_clinicalbert_medical", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bio_clinicalbert_medical| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.6 MB| + +## References + +https://huggingface.co/tarasophia/Bio_ClinicalBERT_medical \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bio_clinicalbert_medical_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-bio_clinicalbert_medical_pipeline_en.md new file mode 100644 index 00000000000000..3867571123e64b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bio_clinicalbert_medical_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English bio_clinicalbert_medical_pipeline pipeline BertForSequenceClassification from tarasophia +author: John Snow Labs +name: bio_clinicalbert_medical_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bio_clinicalbert_medical_pipeline` is a English model originally trained by tarasophia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_medical_pipeline_en_5.5.1_3.0_1731310261467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bio_clinicalbert_medical_pipeline_en_5.5.1_3.0_1731310261467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bio_clinicalbert_medical_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bio_clinicalbert_medical_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bio_clinicalbert_medical_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.6 MB| + +## References + +https://huggingface.co/tarasophia/Bio_ClinicalBERT_medical + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biobert_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-biobert_finetuned_ner_en.md new file mode 100644 index 00000000000000..62bbed3770bcf2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biobert_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English biobert_finetuned_ner BertForTokenClassification from jialinselenasong +author: John Snow Labs +name: biobert_finetuned_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_finetuned_ner` is a English model originally trained by jialinselenasong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_finetuned_ner_en_5.5.1_3.0_1731285895856.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_finetuned_ner_en_5.5.1_3.0_1731285895856.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') + +tokenClassifier = BertForTokenClassification.pretrained("biobert_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("biobert_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobert_finetuned_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/jialinselenasong/biobert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biobert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-biobert_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..ee71f638d2a722 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biobert_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English biobert_finetuned_ner_pipeline pipeline BertForTokenClassification from jialinselenasong +author: John Snow Labs +name: biobert_finetuned_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_finetuned_ner_pipeline` is a English model originally trained by jialinselenasong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_finetuned_ner_pipeline_en_5.5.1_3.0_1731285921161.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_finetuned_ner_pipeline_en_5.5.1_3.0_1731285921161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("biobert_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("biobert_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobert_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/jialinselenasong/biobert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biolinkbert_outcomes_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-biolinkbert_outcomes_ner_en.md new file mode 100644 index 00000000000000..f69fec86f90ffc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biolinkbert_outcomes_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English biolinkbert_outcomes_ner BertForTokenClassification from laiking +author: John Snow Labs +name: biolinkbert_outcomes_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biolinkbert_outcomes_ner` is a English model originally trained by laiking. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biolinkbert_outcomes_ner_en_5.5.1_3.0_1731290874920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biolinkbert_outcomes_ner_en_5.5.1_3.0_1731290874920.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') + +tokenClassifier = BertForTokenClassification.pretrained("biolinkbert_outcomes_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("biolinkbert_outcomes_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biolinkbert_outcomes_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.5 MB| + +## References + +https://huggingface.co/laiking/biolinkbert-outcomes-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biolinkbert_outcomes_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-biolinkbert_outcomes_ner_pipeline_en.md new file mode 100644 index 00000000000000..017d8a8209a313 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biolinkbert_outcomes_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English biolinkbert_outcomes_ner_pipeline pipeline BertForTokenClassification from laiking +author: John Snow Labs +name: biolinkbert_outcomes_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biolinkbert_outcomes_ner_pipeline` is a English model originally trained by laiking. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biolinkbert_outcomes_ner_pipeline_en_5.5.1_3.0_1731290896292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biolinkbert_outcomes_ner_pipeline_en_5.5.1_3.0_1731290896292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("biolinkbert_outcomes_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("biolinkbert_outcomes_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biolinkbert_outcomes_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.5 MB| + +## References + +https://huggingface.co/laiking/biolinkbert-outcomes-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biomed_roberta_all_deep_en.md b/docs/_posts/ahmedlone127/2024-11-11-biomed_roberta_all_deep_en.md new file mode 100644 index 00000000000000..b8ba4c2a86dc3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biomed_roberta_all_deep_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English biomed_roberta_all_deep RoBertaForTokenClassification from jialinselenasong +author: John Snow Labs +name: biomed_roberta_all_deep +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomed_roberta_all_deep` is a English model originally trained by jialinselenasong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomed_roberta_all_deep_en_5.5.1_3.0_1731311373367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomed_roberta_all_deep_en_5.5.1_3.0_1731311373367.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("biomed_roberta_all_deep","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("biomed_roberta_all_deep", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biomed_roberta_all_deep| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|466.3 MB| + +## References + +https://huggingface.co/jialinselenasong/biomed_roberta_all_deep \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_en.md b/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_en.md new file mode 100644 index 00000000000000..80c4b0e0579710 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa BertForSequenceClassification from blizrys +author: John Snow Labs +name: biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa` is a English model originally trained by blizrys. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_en_5.5.1_3.0_1731310162199.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_en_5.5.1_3.0_1731310162199.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("biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.4 MB| + +## References + +https://huggingface.co/blizrys/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en.md new file mode 100644 index 00000000000000..be9d4f6ad69b31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en.md @@ -0,0 +1,72 @@ +--- +layout: model +title: English biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline pipeline BertForSequenceClassification from blizrys +author: John Snow Labs +name: biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline` is a English model originally trained by blizrys. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en_5.5.1_3.0_1731310188434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline_en_5.5.1_3.0_1731310188434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biomednlp_pubmedbert_base_uncased_abstract_fulltext_finetuned_pubmedqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|410.4 MB| + +## References + +References + +https://huggingface.co/blizrys/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_proteinstructure_ner_v2_1_en.md b/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_proteinstructure_ner_v2_1_en.md new file mode 100644 index 00000000000000..c1f7c3868cebd0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_proteinstructure_ner_v2_1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English biomednlp_pubmedbert_proteinstructure_ner_v2_1 BertForTokenClassification from PDBEurope +author: John Snow Labs +name: biomednlp_pubmedbert_proteinstructure_ner_v2_1 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_pubmedbert_proteinstructure_ner_v2_1` is a English model originally trained by PDBEurope. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_proteinstructure_ner_v2_1_en_5.5.1_3.0_1731285743740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_proteinstructure_ner_v2_1_en_5.5.1_3.0_1731285743740.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') + +tokenClassifier = BertForTokenClassification.pretrained("biomednlp_pubmedbert_proteinstructure_ner_v2_1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("biomednlp_pubmedbert_proteinstructure_ner_v2_1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biomednlp_pubmedbert_proteinstructure_ner_v2_1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|408.3 MB| + +## References + +https://huggingface.co/PDBEurope/BiomedNLP-PubMedBERT-ProteinStructure-NER-v2.1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline_en.md new file mode 100644 index 00000000000000..f520348db9181e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline pipeline BertForTokenClassification from PDBEurope +author: John Snow Labs +name: biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline` is a English model originally trained by PDBEurope. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline_en_5.5.1_3.0_1731285765036.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline_en_5.5.1_3.0_1731285765036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biomednlp_pubmedbert_proteinstructure_ner_v2_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.3 MB| + +## References + +https://huggingface.co/PDBEurope/BiomedNLP-PubMedBERT-ProteinStructure-NER-v2.1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_distemist_es.md b/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_distemist_es.md new file mode 100644 index 00000000000000..804ae6163d7309 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_distemist_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish bsc_bio_ehr_spanish_distemist RoBertaForTokenClassification from BSC-NLP4BIA +author: John Snow Labs +name: bsc_bio_ehr_spanish_distemist +date: 2024-11-11 +tags: [es, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_distemist` is a Castilian, Spanish model originally trained by BSC-NLP4BIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_distemist_es_5.5.1_3.0_1731311054905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_distemist_es_5.5.1_3.0_1731311054905.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_distemist","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("bsc_bio_ehr_spanish_distemist", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bsc_bio_ehr_spanish_distemist| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|441.8 MB| + +## References + +https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-distemist \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_distemist_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_distemist_pipeline_es.md new file mode 100644 index 00000000000000..be867693b94b88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_distemist_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bsc_bio_ehr_spanish_distemist_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA +author: John Snow Labs +name: bsc_bio_ehr_spanish_distemist_pipeline +date: 2024-11-11 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_distemist_pipeline` is a Castilian, Spanish model originally trained by BSC-NLP4BIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_distemist_pipeline_es_5.5.1_3.0_1731311079632.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_distemist_pipeline_es_5.5.1_3.0_1731311079632.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_distemist_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_distemist_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bsc_bio_ehr_spanish_distemist_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|441.8 MB| + +## References + +https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-distemist + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_medprocner_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_medprocner_pipeline_es.md new file mode 100644 index 00000000000000..76b4458fe2aa97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-bsc_bio_ehr_spanish_medprocner_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish bsc_bio_ehr_spanish_medprocner_pipeline pipeline RoBertaForTokenClassification from BSC-NLP4BIA +author: John Snow Labs +name: bsc_bio_ehr_spanish_medprocner_pipeline +date: 2024-11-11 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bsc_bio_ehr_spanish_medprocner_pipeline` is a Castilian, Spanish model originally trained by BSC-NLP4BIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_medprocner_pipeline_es_5.5.1_3.0_1731314158801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bsc_bio_ehr_spanish_medprocner_pipeline_es_5.5.1_3.0_1731314158801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("bsc_bio_ehr_spanish_medprocner_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("bsc_bio_ehr_spanish_medprocner_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bsc_bio_ehr_spanish_medprocner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|441.8 MB| + +## References + +https://huggingface.co/BSC-NLP4BIA/bsc-bio-ehr-es-medprocner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-burmese_bert_nepal_bhasa_version_5_0_en.md b/docs/_posts/ahmedlone127/2024-11-11-burmese_bert_nepal_bhasa_version_5_0_en.md new file mode 100644 index 00000000000000..e1f011258cabf7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-burmese_bert_nepal_bhasa_version_5_0_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English burmese_bert_nepal_bhasa_version_5_0 BertForQuestionAnswering from Ashkh0099 +author: John Snow Labs +name: burmese_bert_nepal_bhasa_version_5_0 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`burmese_bert_nepal_bhasa_version_5_0` is a English model originally trained by Ashkh0099. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_bert_nepal_bhasa_version_5_0_en_5.5.1_3.0_1731289220310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_bert_nepal_bhasa_version_5_0_en_5.5.1_3.0_1731289220310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("burmese_bert_nepal_bhasa_version_5_0","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("burmese_bert_nepal_bhasa_version_5_0", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_bert_nepal_bhasa_version_5_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Ashkh0099/my-bert-new-version-5.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-burmese_bert_nepal_bhasa_version_5_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-burmese_bert_nepal_bhasa_version_5_0_pipeline_en.md new file mode 100644 index 00000000000000..210acef151dd59 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-burmese_bert_nepal_bhasa_version_5_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English burmese_bert_nepal_bhasa_version_5_0_pipeline pipeline BertForQuestionAnswering from Ashkh0099 +author: John Snow Labs +name: burmese_bert_nepal_bhasa_version_5_0_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_bert_nepal_bhasa_version_5_0_pipeline` is a English model originally trained by Ashkh0099. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_bert_nepal_bhasa_version_5_0_pipeline_en_5.5.1_3.0_1731289246571.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_bert_nepal_bhasa_version_5_0_pipeline_en_5.5.1_3.0_1731289246571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("burmese_bert_nepal_bhasa_version_5_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("burmese_bert_nepal_bhasa_version_5_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_bert_nepal_bhasa_version_5_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/Ashkh0099/my-bert-new-version-5.0 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-cc_uffs_ppc_ft_test_multiqa_en.md b/docs/_posts/ahmedlone127/2024-11-11-cc_uffs_ppc_ft_test_multiqa_en.md new file mode 100644 index 00000000000000..d2c15b2c8f3562 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-cc_uffs_ppc_ft_test_multiqa_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English cc_uffs_ppc_ft_test_multiqa MPNetEmbeddings from winderfeld +author: John Snow Labs +name: cc_uffs_ppc_ft_test_multiqa +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cc_uffs_ppc_ft_test_multiqa` is a English model originally trained by winderfeld. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cc_uffs_ppc_ft_test_multiqa_en_5.5.1_3.0_1731294914275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cc_uffs_ppc_ft_test_multiqa_en_5.5.1_3.0_1731294914275.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") + +embeddings = MPNetEmbeddings.pretrained("cc_uffs_ppc_ft_test_multiqa","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("cc_uffs_ppc_ft_test_multiqa","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cc_uffs_ppc_ft_test_multiqa| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/winderfeld/cc-uffs-ppc-ft-test-multiqa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-cc_uffs_ppc_ft_test_multiqa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-cc_uffs_ppc_ft_test_multiqa_pipeline_en.md new file mode 100644 index 00000000000000..20f7fe6e43321e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-cc_uffs_ppc_ft_test_multiqa_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English cc_uffs_ppc_ft_test_multiqa_pipeline pipeline MPNetEmbeddings from winderfeld +author: John Snow Labs +name: cc_uffs_ppc_ft_test_multiqa_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cc_uffs_ppc_ft_test_multiqa_pipeline` is a English model originally trained by winderfeld. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cc_uffs_ppc_ft_test_multiqa_pipeline_en_5.5.1_3.0_1731294936076.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cc_uffs_ppc_ft_test_multiqa_pipeline_en_5.5.1_3.0_1731294936076.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cc_uffs_ppc_ft_test_multiqa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cc_uffs_ppc_ft_test_multiqa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cc_uffs_ppc_ft_test_multiqa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/winderfeld/cc-uffs-ppc-ft-test-multiqa + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-celloscope_28000_ner_banglabert_finetuned_en.md b/docs/_posts/ahmedlone127/2024-11-11-celloscope_28000_ner_banglabert_finetuned_en.md new file mode 100644 index 00000000000000..51842560888783 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-celloscope_28000_ner_banglabert_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English celloscope_28000_ner_banglabert_finetuned BertForTokenClassification from celloscopeai +author: John Snow Labs +name: celloscope_28000_ner_banglabert_finetuned +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`celloscope_28000_ner_banglabert_finetuned` is a English model originally trained by celloscopeai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/celloscope_28000_ner_banglabert_finetuned_en_5.5.1_3.0_1731285437232.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/celloscope_28000_ner_banglabert_finetuned_en_5.5.1_3.0_1731285437232.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') + +tokenClassifier = BertForTokenClassification.pretrained("celloscope_28000_ner_banglabert_finetuned","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("celloscope_28000_ner_banglabert_finetuned", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|celloscope_28000_ner_banglabert_finetuned| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/celloscopeai/celloscope-28000-ner-banglabert-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-celloscope_28000_ner_banglabert_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-celloscope_28000_ner_banglabert_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..7e1a76e90d7d71 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-celloscope_28000_ner_banglabert_finetuned_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English celloscope_28000_ner_banglabert_finetuned_pipeline pipeline BertForTokenClassification from celloscopeai +author: John Snow Labs +name: celloscope_28000_ner_banglabert_finetuned_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`celloscope_28000_ner_banglabert_finetuned_pipeline` is a English model originally trained by celloscopeai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/celloscope_28000_ner_banglabert_finetuned_pipeline_en_5.5.1_3.0_1731285459344.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/celloscope_28000_ner_banglabert_finetuned_pipeline_en_5.5.1_3.0_1731285459344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("celloscope_28000_ner_banglabert_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("celloscope_28000_ner_banglabert_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|celloscope_28000_ner_banglabert_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/celloscopeai/celloscope-28000-ner-banglabert-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-checkpoints_almino_en.md b/docs/_posts/ahmedlone127/2024-11-11-checkpoints_almino_en.md new file mode 100644 index 00000000000000..f8b1fef9dc977f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-checkpoints_almino_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English checkpoints_almino WhisperForCTC from almino +author: John Snow Labs +name: checkpoints_almino +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`checkpoints_almino` is a English model originally trained by almino. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoints_almino_en_5.5.1_3.0_1731302964849.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoints_almino_en_5.5.1_3.0_1731302964849.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("checkpoints_almino","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("checkpoints_almino", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|checkpoints_almino| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/almino/checkpoints \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-checkpoints_almino_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-checkpoints_almino_pipeline_en.md new file mode 100644 index 00000000000000..1c0cbd4df4cfab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-checkpoints_almino_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English checkpoints_almino_pipeline pipeline WhisperForCTC from almino +author: John Snow Labs +name: checkpoints_almino_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`checkpoints_almino_pipeline` is a English model originally trained by almino. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/checkpoints_almino_pipeline_en_5.5.1_3.0_1731303059185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/checkpoints_almino_pipeline_en_5.5.1_3.0_1731303059185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("checkpoints_almino_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("checkpoints_almino_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|checkpoints_almino_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/almino/checkpoints + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-chinese_roberta_wwm_ext_large_en.md b/docs/_posts/ahmedlone127/2024-11-11-chinese_roberta_wwm_ext_large_en.md new file mode 100644 index 00000000000000..272cf1815a1730 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-chinese_roberta_wwm_ext_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English chinese_roberta_wwm_ext_large BertForTokenClassification from agdsga +author: John Snow Labs +name: chinese_roberta_wwm_ext_large +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_roberta_wwm_ext_large` is a English model originally trained by agdsga. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_large_en_5.5.1_3.0_1731291105667.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_large_en_5.5.1_3.0_1731291105667.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') + +tokenClassifier = BertForTokenClassification.pretrained("chinese_roberta_wwm_ext_large","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("chinese_roberta_wwm_ext_large", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_wwm_ext_large| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/agdsga/chinese-roberta-wwm-ext-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-chinese_roberta_wwm_ext_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-chinese_roberta_wwm_ext_large_pipeline_en.md new file mode 100644 index 00000000000000..e49d1eba0e6fd0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-chinese_roberta_wwm_ext_large_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English chinese_roberta_wwm_ext_large_pipeline pipeline BertForTokenClassification from agdsga +author: John Snow Labs +name: chinese_roberta_wwm_ext_large_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_roberta_wwm_ext_large_pipeline` is a English model originally trained by agdsga. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_large_pipeline_en_5.5.1_3.0_1731291172017.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_large_pipeline_en_5.5.1_3.0_1731291172017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("chinese_roberta_wwm_ext_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("chinese_roberta_wwm_ext_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_wwm_ext_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/agdsga/chinese-roberta-wwm-ext-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-classify_bluesky_1000_v2_en.md b/docs/_posts/ahmedlone127/2024-11-11-classify_bluesky_1000_v2_en.md new file mode 100644 index 00000000000000..52d890d42c048a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-classify_bluesky_1000_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English classify_bluesky_1000_v2 AlbertForSequenceClassification from Himanshu99001 +author: John Snow Labs +name: classify_bluesky_1000_v2 +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, albert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: AlbertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classify_bluesky_1000_v2` is a English model originally trained by Himanshu99001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classify_bluesky_1000_v2_en_5.5.1_3.0_1731296867467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classify_bluesky_1000_v2_en_5.5.1_3.0_1731296867467.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 = AlbertForSequenceClassification.pretrained("classify_bluesky_1000_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = AlbertForSequenceClassification.pretrained("classify_bluesky_1000_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classify_bluesky_1000_v2| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/Himanshu99001/classify-bluesky-1000-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-classify_bluesky_1000_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-classify_bluesky_1000_v2_pipeline_en.md new file mode 100644 index 00000000000000..fcfea659489bba --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-classify_bluesky_1000_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English classify_bluesky_1000_v2_pipeline pipeline AlbertForSequenceClassification from Himanshu99001 +author: John Snow Labs +name: classify_bluesky_1000_v2_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained AlbertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`classify_bluesky_1000_v2_pipeline` is a English model originally trained by Himanshu99001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/classify_bluesky_1000_v2_pipeline_en_5.5.1_3.0_1731296869891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/classify_bluesky_1000_v2_pipeline_en_5.5.1_3.0_1731296869891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("classify_bluesky_1000_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("classify_bluesky_1000_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|classify_bluesky_1000_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|44.2 MB| + +## References + +https://huggingface.co/Himanshu99001/classify-bluesky-1000-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- AlbertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_base_unsupervised_en.md b/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_base_unsupervised_en.md new file mode 100644 index 00000000000000..44f53fb5b1fd00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_base_unsupervised_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English cleaned_e5_base_unsupervised E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_base_unsupervised +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_base_unsupervised` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_en_5.5.1_3.0_1731300058597.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_en_5.5.1_3.0_1731300058597.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") + +embeddings = E5Embeddings.pretrained("cleaned_e5_base_unsupervised","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("cleaned_e5_base_unsupervised","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_base_unsupervised| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|386.2 MB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-base-unsupervised \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_base_unsupervised_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_base_unsupervised_pipeline_en.md new file mode 100644 index 00000000000000..5f3facfd1ca268 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_base_unsupervised_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English cleaned_e5_base_unsupervised_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_base_unsupervised_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_base_unsupervised_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_pipeline_en_5.5.1_3.0_1731300087523.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_base_unsupervised_pipeline_en_5.5.1_3.0_1731300087523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cleaned_e5_base_unsupervised_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cleaned_e5_base_unsupervised_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_base_unsupervised_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|386.2 MB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-base-unsupervised + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_large_unsupervised_en.md b/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_large_unsupervised_en.md new file mode 100644 index 00000000000000..6901e54313ff7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_large_unsupervised_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English cleaned_e5_large_unsupervised E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_large_unsupervised +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_large_unsupervised` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_large_unsupervised_en_5.5.1_3.0_1731300839857.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_large_unsupervised_en_5.5.1_3.0_1731300839857.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") + +embeddings = E5Embeddings.pretrained("cleaned_e5_large_unsupervised","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("cleaned_e5_large_unsupervised","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_large_unsupervised| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-large-unsupervised \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_large_unsupervised_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_large_unsupervised_pipeline_en.md new file mode 100644 index 00000000000000..3e2cad6a59a779 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-cleaned_e5_large_unsupervised_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English cleaned_e5_large_unsupervised_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: cleaned_e5_large_unsupervised_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cleaned_e5_large_unsupervised_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cleaned_e5_large_unsupervised_pipeline_en_5.5.1_3.0_1731300911401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cleaned_e5_large_unsupervised_pipeline_en_5.5.1_3.0_1731300911401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("cleaned_e5_large_unsupervised_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("cleaned_e5_large_unsupervised_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cleaned_e5_large_unsupervised_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/rithwik-db/cleaned-e5-large-unsupervised + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-climateattention_ctw_en.md b/docs/_posts/ahmedlone127/2024-11-11-climateattention_ctw_en.md new file mode 100644 index 00000000000000..63a80ebbcd8fbc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-climateattention_ctw_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English climateattention_ctw RoBertaForTokenClassification from kruthof +author: John Snow Labs +name: climateattention_ctw +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climateattention_ctw` is a English model originally trained by kruthof. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climateattention_ctw_en_5.5.1_3.0_1731311348537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climateattention_ctw_en_5.5.1_3.0_1731311348537.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("climateattention_ctw","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("climateattention_ctw", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|climateattention_ctw| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|307.4 MB| + +## References + +https://huggingface.co/kruthof/climateattention-ctw \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-climateattention_ctw_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-climateattention_ctw_pipeline_en.md new file mode 100644 index 00000000000000..9201831e6ece88 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-climateattention_ctw_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English climateattention_ctw_pipeline pipeline RoBertaForTokenClassification from kruthof +author: John Snow Labs +name: climateattention_ctw_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`climateattention_ctw_pipeline` is a English model originally trained by kruthof. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/climateattention_ctw_pipeline_en_5.5.1_3.0_1731311365014.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/climateattention_ctw_pipeline_en_5.5.1_3.0_1731311365014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("climateattention_ctw_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("climateattention_ctw_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|climateattention_ctw_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|307.4 MB| + +## References + +https://huggingface.co/kruthof/climateattention-ctw + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-clinical_trial_termination_en.md b/docs/_posts/ahmedlone127/2024-11-11-clinical_trial_termination_en.md new file mode 100644 index 00000000000000..74d7c04df010c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-clinical_trial_termination_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English clinical_trial_termination BertForSequenceClassification from clem21chan +author: John Snow Labs +name: clinical_trial_termination +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinical_trial_termination` is a English model originally trained by clem21chan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinical_trial_termination_en_5.5.1_3.0_1731309477045.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinical_trial_termination_en_5.5.1_3.0_1731309477045.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("clinical_trial_termination","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("clinical_trial_termination", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinical_trial_termination| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.5 MB| + +## References + +https://huggingface.co/clem21chan/clinical_trial_termination \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-clinical_trial_termination_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-clinical_trial_termination_pipeline_en.md new file mode 100644 index 00000000000000..aeee5a4a1cac2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-clinical_trial_termination_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English clinical_trial_termination_pipeline pipeline BertForSequenceClassification from clem21chan +author: John Snow Labs +name: clinical_trial_termination_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`clinical_trial_termination_pipeline` is a English model originally trained by clem21chan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/clinical_trial_termination_pipeline_en_5.5.1_3.0_1731309500897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/clinical_trial_termination_pipeline_en_5.5.1_3.0_1731309500897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("clinical_trial_termination_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("clinical_trial_termination_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|clinical_trial_termination_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.6 MB| + +## References + +https://huggingface.co/clem21chan/clinical_trial_termination + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-deberta_v3_large_lemon_spell_5k_en.md b/docs/_posts/ahmedlone127/2024-11-11-deberta_v3_large_lemon_spell_5k_en.md new file mode 100644 index 00000000000000..2cdc1db3189282 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-deberta_v3_large_lemon_spell_5k_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deberta_v3_large_lemon_spell_5k DeBertaForTokenClassification from manred1997 +author: John Snow Labs +name: deberta_v3_large_lemon_spell_5k +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, deberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DeBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_lemon_spell_5k` is a English model originally trained by manred1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_lemon_spell_5k_en_5.5.1_3.0_1731306834489.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_lemon_spell_5k_en_5.5.1_3.0_1731306834489.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') + +tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_lemon_spell_5k","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = DeBertaForTokenClassification.pretrained("deberta_v3_large_lemon_spell_5k", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_lemon_spell_5k| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/manred1997/deberta-v3-large-lemon-spell_5k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-deberta_v3_large_lemon_spell_5k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-deberta_v3_large_lemon_spell_5k_pipeline_en.md new file mode 100644 index 00000000000000..e765205041dfb1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-deberta_v3_large_lemon_spell_5k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deberta_v3_large_lemon_spell_5k_pipeline pipeline DeBertaForTokenClassification from manred1997 +author: John Snow Labs +name: deberta_v3_large_lemon_spell_5k_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DeBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deberta_v3_large_lemon_spell_5k_pipeline` is a English model originally trained by manred1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deberta_v3_large_lemon_spell_5k_pipeline_en_5.5.1_3.0_1731306916759.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deberta_v3_large_lemon_spell_5k_pipeline_en_5.5.1_3.0_1731306916759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deberta_v3_large_lemon_spell_5k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deberta_v3_large_lemon_spell_5k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deberta_v3_large_lemon_spell_5k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/manred1997/deberta-v3-large-lemon-spell_5k + +## Included Models + +- DocumentAssembler +- TokenizerModel +- DeBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-deeppavlov_absa_en.md b/docs/_posts/ahmedlone127/2024-11-11-deeppavlov_absa_en.md new file mode 100644 index 00000000000000..7a78ee7b43d0e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-deeppavlov_absa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English deeppavlov_absa XlmRoBertaForTokenClassification from natriistorm +author: John Snow Labs +name: deeppavlov_absa +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deeppavlov_absa` is a English model originally trained by natriistorm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deeppavlov_absa_en_5.5.1_3.0_1731292999917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deeppavlov_absa_en_5.5.1_3.0_1731292999917.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') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("deeppavlov_absa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("deeppavlov_absa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deeppavlov_absa| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|857.1 MB| + +## References + +https://huggingface.co/natriistorm/DeepPavlov-ABSA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-deeppavlov_absa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-deeppavlov_absa_pipeline_en.md new file mode 100644 index 00000000000000..6a9194d07a8233 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-deeppavlov_absa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English deeppavlov_absa_pipeline pipeline XlmRoBertaForTokenClassification from natriistorm +author: John Snow Labs +name: deeppavlov_absa_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deeppavlov_absa_pipeline` is a English model originally trained by natriistorm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deeppavlov_absa_pipeline_en_5.5.1_3.0_1731293111760.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deeppavlov_absa_pipeline_en_5.5.1_3.0_1731293111760.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("deeppavlov_absa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("deeppavlov_absa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deeppavlov_absa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|857.1 MB| + +## References + +https://huggingface.co/natriistorm/DeepPavlov-ABSA + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-distilhubert_korean_zeroth_ko.md b/docs/_posts/ahmedlone127/2024-11-11-distilhubert_korean_zeroth_ko.md new file mode 100644 index 00000000000000..bd77dc0a180729 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-distilhubert_korean_zeroth_ko.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Korean distilhubert_korean_zeroth HubertForCTC from Bingsu +author: John Snow Labs +name: distilhubert_korean_zeroth +date: 2024-11-11 +tags: [ko, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: ko +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilhubert_korean_zeroth` is a Korean model originally trained by Bingsu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilhubert_korean_zeroth_ko_5.5.1_3.0_1731285005655.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilhubert_korean_zeroth_ko_5.5.1_3.0_1731285005655.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 = HubertForCTC.pretrained("distilhubert_korean_zeroth","ko") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("distilhubert_korean_zeroth", "ko") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilhubert_korean_zeroth| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ko| +|Size:|183.5 MB| + +## References + +https://huggingface.co/Bingsu/distilhubert-ko-zeroth \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-distilhubert_korean_zeroth_pipeline_ko.md b/docs/_posts/ahmedlone127/2024-11-11-distilhubert_korean_zeroth_pipeline_ko.md new file mode 100644 index 00000000000000..e0de5f10ccf087 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-distilhubert_korean_zeroth_pipeline_ko.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Korean distilhubert_korean_zeroth_pipeline pipeline HubertForCTC from Bingsu +author: John Snow Labs +name: distilhubert_korean_zeroth_pipeline +date: 2024-11-11 +tags: [ko, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ko +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilhubert_korean_zeroth_pipeline` is a Korean model originally trained by Bingsu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilhubert_korean_zeroth_pipeline_ko_5.5.1_3.0_1731285014876.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilhubert_korean_zeroth_pipeline_ko_5.5.1_3.0_1731285014876.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("distilhubert_korean_zeroth_pipeline", lang = "ko") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("distilhubert_korean_zeroth_pipeline", lang = "ko") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilhubert_korean_zeroth_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ko| +|Size:|183.5 MB| + +## References + +https://huggingface.co/Bingsu/distilhubert-ko-zeroth + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-e5_base_en.md b/docs/_posts/ahmedlone127/2024-11-11-e5_base_en.md new file mode 100644 index 00000000000000..d945cfebc6a6ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-e5_base_en.md @@ -0,0 +1,67 @@ +--- +layout: model +title: E5 Base Sentence Embeddings +author: John Snow Labs +name: e5_base +date: 2024-11-11 +tags: [en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022 + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_en_5.5.1_3.0_1731300102963.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_en_5.5.1_3.0_1731300102963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings =E5Embeddings.pretrained("e5_base","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("instructor") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) +``` +```scala +val embeddings = E5Embeddings.pretrained("e5_base","en") + .setInputCols(["document"]) + .setOutputCol("e5_embeddings") +val pipeline = new Pipeline().setStages(Array(document, embeddings)) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|258.6 MB| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-e5_base_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-e5_base_pipeline_en.md new file mode 100644 index 00000000000000..714ee62884d867 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-e5_base_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English e5_base_pipeline pipeline E5Embeddings from intfloat +author: John Snow Labs +name: e5_base_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_base_pipeline` is a English model originally trained by intfloat. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_base_pipeline_en_5.5.1_3.0_1731300180105.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_base_pipeline_en_5.5.1_3.0_1731300180105.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("e5_base_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("e5_base_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|258.6 MB| + +## References + +References + +https://huggingface.co/intfloat/e5-base + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-e5_large_en.md b/docs/_posts/ahmedlone127/2024-11-11-e5_large_en.md new file mode 100644 index 00000000000000..d4a5086d2ecfb6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-e5_large_en.md @@ -0,0 +1,75 @@ +--- +layout: model +title: E5 Large Sentence Embeddings +author: John Snow Labs +name: e5_large +date: 2024-11-11 +tags: [en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022 + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_en_5.5.1_3.0_1731300299067.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_en_5.5.1_3.0_1731300299067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings =E5Embeddings.pretrained("e5_large","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("instructor") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) +``` +```scala +val embeddings = E5Embeddings.pretrained("e5_large","en") + .setInputCols(["document"]) + .setOutputCol("e5_embeddings") +val pipeline = new Pipeline().setStages(Array(document, embeddings)) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|796.1 MB| + +## References + +References + +References + +https://huggingface.co/intfloat/e5-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-e5_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-e5_large_pipeline_en.md new file mode 100644 index 00000000000000..467e23d43eac59 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-e5_large_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English e5_large_pipeline pipeline E5Embeddings from intfloat +author: John Snow Labs +name: e5_large_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_large_pipeline` is a English model originally trained by intfloat. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_large_pipeline_en_5.5.1_3.0_1731300535649.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_large_pipeline_en_5.5.1_3.0_1731300535649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("e5_large_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("e5_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|796.1 MB| + +## References + +References + +https://huggingface.co/intfloat/e5-large + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-e5_small_en.md b/docs/_posts/ahmedlone127/2024-11-11-e5_small_en.md new file mode 100644 index 00000000000000..090b3563e10d8c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-e5_small_en.md @@ -0,0 +1,67 @@ +--- +layout: model +title: E5 Small Sentence Embeddings +author: John Snow Labs +name: e5_small +date: 2024-11-11 +tags: [en, open_source, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022 + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_en_5.5.1_3.0_1731300044693.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_en_5.5.1_3.0_1731300044693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +embeddings =E5Embeddings.pretrained("e5_small","en") \ + .setInputCols(["documents"]) \ + .setOutputCol("instructor") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) +``` +```scala +val embeddings = E5Embeddings.pretrained("e5_small","en") + .setInputCols(["document"]) + .setOutputCol("e5_embeddings") +val pipeline = new Pipeline().setStages(Array(document, embeddings)) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_small| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|79.9 MB| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-e5_small_lora_ai_generated_detector_en.md b/docs/_posts/ahmedlone127/2024-11-11-e5_small_lora_ai_generated_detector_en.md new file mode 100644 index 00000000000000..a3d9ef09ef1bb5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-e5_small_lora_ai_generated_detector_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English e5_small_lora_ai_generated_detector BertForSequenceClassification from MayZhou +author: John Snow Labs +name: e5_small_lora_ai_generated_detector +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_lora_ai_generated_detector` is a English model originally trained by MayZhou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_lora_ai_generated_detector_en_5.5.1_3.0_1731309372403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_lora_ai_generated_detector_en_5.5.1_3.0_1731309372403.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("e5_small_lora_ai_generated_detector","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("e5_small_lora_ai_generated_detector", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_small_lora_ai_generated_detector| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|87.5 MB| + +## References + +https://huggingface.co/MayZhou/e5-small-lora-ai-generated-detector \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-e5_small_lora_ai_generated_detector_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-e5_small_lora_ai_generated_detector_pipeline_en.md new file mode 100644 index 00000000000000..436ceffa5f5f5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-e5_small_lora_ai_generated_detector_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English e5_small_lora_ai_generated_detector_pipeline pipeline BertForSequenceClassification from MayZhou +author: John Snow Labs +name: e5_small_lora_ai_generated_detector_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_lora_ai_generated_detector_pipeline` is a English model originally trained by MayZhou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_lora_ai_generated_detector_pipeline_en_5.5.1_3.0_1731309394398.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_lora_ai_generated_detector_pipeline_en_5.5.1_3.0_1731309394398.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("e5_small_lora_ai_generated_detector_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("e5_small_lora_ai_generated_detector_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_small_lora_ai_generated_detector_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|87.5 MB| + +## References + +https://huggingface.co/MayZhou/e5-small-lora-ai-generated-detector + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-e5_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-e5_small_pipeline_en.md new file mode 100644 index 00000000000000..598d42aa0fb9d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-e5_small_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English e5_small_pipeline pipeline E5Embeddings from intfloat +author: John Snow Labs +name: e5_small_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`e5_small_pipeline` is a English model originally trained by intfloat. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/e5_small_pipeline_en_5.5.1_3.0_1731300067905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/e5_small_pipeline_en_5.5.1_3.0_1731300067905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("e5_small_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("e5_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|e5_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|79.9 MB| + +## References + +References + +https://huggingface.co/intfloat/e5-small + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-embedded_e5_base_50_en.md b/docs/_posts/ahmedlone127/2024-11-11-embedded_e5_base_50_en.md new file mode 100644 index 00000000000000..06bcc9d7228d04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-embedded_e5_base_50_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English embedded_e5_base_50 E5Embeddings from rithwik-db +author: John Snow Labs +name: embedded_e5_base_50 +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, e5] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: E5Embeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedded_e5_base_50` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedded_e5_base_50_en_5.5.1_3.0_1731300053310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedded_e5_base_50_en_5.5.1_3.0_1731300053310.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") + +embeddings = E5Embeddings.pretrained("embedded_e5_base_50","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = E5Embeddings.pretrained("embedded_e5_base_50","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|embedded_e5_base_50| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[E5]| +|Language:|en| +|Size:|379.2 MB| + +## References + +https://huggingface.co/rithwik-db/embedded-e5-base-50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-embedded_e5_base_50_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-embedded_e5_base_50_pipeline_en.md new file mode 100644 index 00000000000000..de6a205a9ba28d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-embedded_e5_base_50_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English embedded_e5_base_50_pipeline pipeline E5Embeddings from rithwik-db +author: John Snow Labs +name: embedded_e5_base_50_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained E5Embeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`embedded_e5_base_50_pipeline` is a English model originally trained by rithwik-db. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/embedded_e5_base_50_pipeline_en_5.5.1_3.0_1731300084750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/embedded_e5_base_50_pipeline_en_5.5.1_3.0_1731300084750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("embedded_e5_base_50_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("embedded_e5_base_50_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|embedded_e5_base_50_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|379.3 MB| + +## References + +https://huggingface.co/rithwik-db/embedded-e5-base-50 + +## Included Models + +- DocumentAssembler +- E5Embeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_german_hubert_s921_de.md b/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_german_hubert_s921_de.md new file mode 100644 index 00000000000000..abaaf8a40c5363 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_german_hubert_s921_de.md @@ -0,0 +1,84 @@ +--- +layout: model +title: German exp_w2v2t_german_hubert_s921 HubertForCTC from jonatasgrosman +author: John Snow Labs +name: exp_w2v2t_german_hubert_s921 +date: 2024-11-11 +tags: [de, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: de +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_german_hubert_s921` is a German model originally trained by jonatasgrosman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_german_hubert_s921_de_5.5.1_3.0_1731286788135.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_german_hubert_s921_de_5.5.1_3.0_1731286788135.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 = HubertForCTC.pretrained("exp_w2v2t_german_hubert_s921","de") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("exp_w2v2t_german_hubert_s921", "de") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|exp_w2v2t_german_hubert_s921| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|de| +|Size:|2.4 GB| + +## References + +https://huggingface.co/jonatasgrosman/exp_w2v2t_de_hubert_s921 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_german_hubert_s921_pipeline_de.md b/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_german_hubert_s921_pipeline_de.md new file mode 100644 index 00000000000000..688625ff61f30b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_german_hubert_s921_pipeline_de.md @@ -0,0 +1,69 @@ +--- +layout: model +title: German exp_w2v2t_german_hubert_s921_pipeline pipeline HubertForCTC from jonatasgrosman +author: John Snow Labs +name: exp_w2v2t_german_hubert_s921_pipeline +date: 2024-11-11 +tags: [de, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: de +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_german_hubert_s921_pipeline` is a German model originally trained by jonatasgrosman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_german_hubert_s921_pipeline_de_5.5.1_3.0_1731286902986.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_german_hubert_s921_pipeline_de_5.5.1_3.0_1731286902986.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("exp_w2v2t_german_hubert_s921_pipeline", lang = "de") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("exp_w2v2t_german_hubert_s921_pipeline", lang = "de") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|exp_w2v2t_german_hubert_s921_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|2.4 GB| + +## References + +https://huggingface.co/jonatasgrosman/exp_w2v2t_de_hubert_s921 + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_persian_farsi_hubert_s889_fa.md b/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_persian_farsi_hubert_s889_fa.md new file mode 100644 index 00000000000000..f1767a4b5e2d37 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_persian_farsi_hubert_s889_fa.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Persian exp_w2v2t_persian_farsi_hubert_s889 HubertForCTC from jonatasgrosman +author: John Snow Labs +name: exp_w2v2t_persian_farsi_hubert_s889 +date: 2024-11-11 +tags: [fa, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: fa +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_persian_farsi_hubert_s889` is a Persian model originally trained by jonatasgrosman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_persian_farsi_hubert_s889_fa_5.5.1_3.0_1731283735194.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_persian_farsi_hubert_s889_fa_5.5.1_3.0_1731283735194.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 = HubertForCTC.pretrained("exp_w2v2t_persian_farsi_hubert_s889","fa") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("exp_w2v2t_persian_farsi_hubert_s889", "fa") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|exp_w2v2t_persian_farsi_hubert_s889| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|fa| +|Size:|2.4 GB| + +## References + +https://huggingface.co/jonatasgrosman/exp_w2v2t_fa_hubert_s889 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_persian_farsi_hubert_s889_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_persian_farsi_hubert_s889_pipeline_fa.md new file mode 100644 index 00000000000000..f8a5b94d21856f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-exp_w2v2t_persian_farsi_hubert_s889_pipeline_fa.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Persian exp_w2v2t_persian_farsi_hubert_s889_pipeline pipeline HubertForCTC from jonatasgrosman +author: John Snow Labs +name: exp_w2v2t_persian_farsi_hubert_s889_pipeline +date: 2024-11-11 +tags: [fa, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: fa +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`exp_w2v2t_persian_farsi_hubert_s889_pipeline` is a Persian model originally trained by jonatasgrosman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/exp_w2v2t_persian_farsi_hubert_s889_pipeline_fa_5.5.1_3.0_1731283877387.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/exp_w2v2t_persian_farsi_hubert_s889_pipeline_fa_5.5.1_3.0_1731283877387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("exp_w2v2t_persian_farsi_hubert_s889_pipeline", lang = "fa") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("exp_w2v2t_persian_farsi_hubert_s889_pipeline", lang = "fa") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|exp_w2v2t_persian_farsi_hubert_s889_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|fa| +|Size:|2.4 GB| + +## References + +https://huggingface.co/jonatasgrosman/exp_w2v2t_fa_hubert_s889 + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fab_ramy_v1_en.md b/docs/_posts/ahmedlone127/2024-11-11-fab_ramy_v1_en.md new file mode 100644 index 00000000000000..5232e8bf3394d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fab_ramy_v1_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fab_ramy_v1 MPNetEmbeddings from qinxianliu +author: John Snow Labs +name: fab_ramy_v1 +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fab_ramy_v1` is a English model originally trained by qinxianliu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fab_ramy_v1_en_5.5.1_3.0_1731294774877.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fab_ramy_v1_en_5.5.1_3.0_1731294774877.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") + +embeddings = MPNetEmbeddings.pretrained("fab_ramy_v1","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("fab_ramy_v1","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fab_ramy_v1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/qinxianliu/FAB-Ramy-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fab_ramy_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-fab_ramy_v1_pipeline_en.md new file mode 100644 index 00000000000000..ec125add711018 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fab_ramy_v1_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fab_ramy_v1_pipeline pipeline MPNetEmbeddings from qinxianliu +author: John Snow Labs +name: fab_ramy_v1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fab_ramy_v1_pipeline` is a English model originally trained by qinxianliu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fab_ramy_v1_pipeline_en_5.5.1_3.0_1731294796154.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fab_ramy_v1_pipeline_en_5.5.1_3.0_1731294796154.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fab_ramy_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fab_ramy_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fab_ramy_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/qinxianliu/FAB-Ramy-v1 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-factuality_model_en.md b/docs/_posts/ahmedlone127/2024-11-11-factuality_model_en.md new file mode 100644 index 00000000000000..0d89b27c77db7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-factuality_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English factuality_model BertForSequenceClassification from gljj +author: John Snow Labs +name: factuality_model +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`factuality_model` is a English model originally trained by gljj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/factuality_model_en_5.5.1_3.0_1731309550709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/factuality_model_en_5.5.1_3.0_1731309550709.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("factuality_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("factuality_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|factuality_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gljj/factuality-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-factuality_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-factuality_model_pipeline_en.md new file mode 100644 index 00000000000000..029a7e3f16c80e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-factuality_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English factuality_model_pipeline pipeline BertForSequenceClassification from gljj +author: John Snow Labs +name: factuality_model_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`factuality_model_pipeline` is a English model originally trained by gljj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/factuality_model_pipeline_en_5.5.1_3.0_1731309573179.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/factuality_model_pipeline_en_5.5.1_3.0_1731309573179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("factuality_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("factuality_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|factuality_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gljj/factuality-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fashion_clip_inference_en.md b/docs/_posts/ahmedlone127/2024-11-11-fashion_clip_inference_en.md new file mode 100644 index 00000000000000..b9d41b4fbd0961 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fashion_clip_inference_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English fashion_clip_inference CLIPForZeroShotClassification from Fluf22 +author: John Snow Labs +name: fashion_clip_inference +date: 2024-11-11 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_clip_inference` is a English model originally trained by Fluf22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_clip_inference_en_5.5.1_3.0_1731287432963.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_clip_inference_en_5.5.1_3.0_1731287432963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_clip_inference","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("fashion_clip_inference","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_clip_inference| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/Fluf22/fashion-clip-inference \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fashion_clip_inference_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-fashion_clip_inference_pipeline_en.md new file mode 100644 index 00000000000000..65e5dac4959c25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fashion_clip_inference_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fashion_clip_inference_pipeline pipeline CLIPForZeroShotClassification from Fluf22 +author: John Snow Labs +name: fashion_clip_inference_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fashion_clip_inference_pipeline` is a English model originally trained by Fluf22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fashion_clip_inference_pipeline_en_5.5.1_3.0_1731287527759.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fashion_clip_inference_pipeline_en_5.5.1_3.0_1731287527759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fashion_clip_inference_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fashion_clip_inference_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fashion_clip_inference_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|397.7 MB| + +## References + +https://huggingface.co/Fluf22/fashion-clip-inference + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_bge_large_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_bge_large_en.md new file mode 100644 index 00000000000000..e11b067a8a7785 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_bge_large_en.md @@ -0,0 +1,87 @@ +--- +layout: model +title: English fine_tuned_bge_large BGEEmbeddings from VaggP +author: John Snow Labs +name: fine_tuned_bge_large +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, bge] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BGEEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bge_large` is a English model originally trained by VaggP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_large_en_5.5.1_3.0_1731313695765.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_large_en_5.5.1_3.0_1731313695765.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") + +embeddings = BGEEmbeddings.pretrained("fine_tuned_bge_large","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + + +val embeddings = BGEEmbeddings.pretrained("fine_tuned_bge_large","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp).toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bge_large| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[bge]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/VaggP/fine-tuned-bge-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_bge_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_bge_large_pipeline_en.md new file mode 100644 index 00000000000000..757152937ee2a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_bge_large_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_bge_large_pipeline pipeline BGEEmbeddings from VaggP +author: John Snow Labs +name: fine_tuned_bge_large_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_bge_large_pipeline` is a English model originally trained by VaggP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_large_pipeline_en_5.5.1_3.0_1731313768340.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_bge_large_pipeline_en_5.5.1_3.0_1731313768340.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_bge_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_bge_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_bge_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/VaggP/fine-tuned-bge-large + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_en.md new file mode 100644 index 00000000000000..373910cc722f33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05 BertForQuestionAnswering from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_en_5.5.1_3.0_1731288819872.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_en_5.5.1_3.0_1731288819872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-DatasetQAS-IDK-MRC-with-indobert-large-p2-with-ITTL-with-freeze-LR-1e-05 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline_en.md new file mode 100644 index 00000000000000..e12fac29b141f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline pipeline BertForQuestionAnswering from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline_en_5.5.1_3.0_1731288888810.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline_en_5.5.1_3.0_1731288888810.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_datasetqas_idk_mrc_with_indobert_large_p2_with_ittl_with_freeze_lr_1e_05_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-DatasetQAS-IDK-MRC-with-indobert-large-p2-with-ITTL-with-freeze-LR-1e-05 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_metaphor_detection_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_metaphor_detection_en.md new file mode 100644 index 00000000000000..4ee03c04d84b8f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_metaphor_detection_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English fine_tuned_metaphor_detection BertForSequenceClassification from Sasidhar1826 +author: John Snow Labs +name: fine_tuned_metaphor_detection +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_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_metaphor_detection` is a English model originally trained by Sasidhar1826. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_metaphor_detection_en_5.5.1_3.0_1731309326875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_metaphor_detection_en_5.5.1_3.0_1731309326875.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("fine_tuned_metaphor_detection","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_metaphor_detection", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_metaphor_detection| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Sasidhar1826/fine-tuned-metaphor-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_metaphor_detection_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_metaphor_detection_pipeline_en.md new file mode 100644 index 00000000000000..17786ff6b61d0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_metaphor_detection_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English fine_tuned_metaphor_detection_pipeline pipeline BertForSequenceClassification from Sasidhar1826 +author: John Snow Labs +name: fine_tuned_metaphor_detection_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_metaphor_detection_pipeline` is a English model originally trained by Sasidhar1826. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_metaphor_detection_pipeline_en_5.5.1_3.0_1731309349158.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_metaphor_detection_pipeline_en_5.5.1_3.0_1731309349158.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_metaphor_detection_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_metaphor_detection_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_metaphor_detection_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Sasidhar1826/fine-tuned-metaphor-detection + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_model_resume_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_model_resume_en.md new file mode 100644 index 00000000000000..d17011b2be0e65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_model_resume_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_model_resume MPNetEmbeddings from chamalbistec +author: John Snow Labs +name: fine_tuned_model_resume +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_model_resume` is a English model originally trained by chamalbistec. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_model_resume_en_5.5.1_3.0_1731294871924.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_model_resume_en_5.5.1_3.0_1731294871924.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") + +embeddings = MPNetEmbeddings.pretrained("fine_tuned_model_resume","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("fine_tuned_model_resume","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_model_resume| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/chamalbistec/fine-tuned-model-resume \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_model_resume_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_model_resume_pipeline_en.md new file mode 100644 index 00000000000000..bb0960d9de45d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_model_resume_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_model_resume_pipeline pipeline MPNetEmbeddings from chamalbistec +author: John Snow Labs +name: fine_tuned_model_resume_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_model_resume_pipeline` is a English model originally trained by chamalbistec. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_model_resume_pipeline_en_5.5.1_3.0_1731294897314.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_model_resume_pipeline_en_5.5.1_3.0_1731294897314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_model_resume_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_model_resume_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_model_resume_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/chamalbistec/fine-tuned-model-resume + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_mpnet_model_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_mpnet_model_en.md new file mode 100644 index 00000000000000..72e94d2f098f26 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_mpnet_model_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fine_tuned_mpnet_model MPNetEmbeddings from adityasajja6 +author: John Snow Labs +name: fine_tuned_mpnet_model +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_mpnet_model` is a English model originally trained by adityasajja6. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_mpnet_model_en_5.5.1_3.0_1731294702635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_mpnet_model_en_5.5.1_3.0_1731294702635.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") + +embeddings = MPNetEmbeddings.pretrained("fine_tuned_mpnet_model","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("fine_tuned_mpnet_model","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_mpnet_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/adityasajja6/fine_tuned_mpnet_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_mpnet_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_mpnet_model_pipeline_en.md new file mode 100644 index 00000000000000..386ac09a149993 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fine_tuned_mpnet_model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fine_tuned_mpnet_model_pipeline pipeline MPNetEmbeddings from adityasajja6 +author: John Snow Labs +name: fine_tuned_mpnet_model_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_mpnet_model_pipeline` is a English model originally trained by adityasajja6. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_mpnet_model_pipeline_en_5.5.1_3.0_1731294728871.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_mpnet_model_pipeline_en_5.5.1_3.0_1731294728871.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fine_tuned_mpnet_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fine_tuned_mpnet_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_mpnet_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/adityasajja6/fine_tuned_mpnet_model + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-finetuned_baai_bge_base_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-finetuned_baai_bge_base_english_pipeline_en.md new file mode 100644 index 00000000000000..0bbb8d7b5faf31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-finetuned_baai_bge_base_english_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetuned_baai_bge_base_english_pipeline pipeline BGEEmbeddings from ivanleomk +author: John Snow Labs +name: finetuned_baai_bge_base_english_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_baai_bge_base_english_pipeline` is a English model originally trained by ivanleomk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_baai_bge_base_english_pipeline_en_5.5.1_3.0_1731312762847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_baai_bge_base_english_pipeline_en_5.5.1_3.0_1731312762847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_baai_bge_base_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_baai_bge_base_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_baai_bge_base_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|376.1 MB| + +## References + +https://huggingface.co/ivanleomk/finetuned-BAAI-bge-base-en + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-finetuned_bge_base_english_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-finetuned_bge_base_english_pipeline_en.md new file mode 100644 index 00000000000000..05ea6358173bfa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-finetuned_bge_base_english_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetuned_bge_base_english_pipeline pipeline BGEEmbeddings from ivanleomk +author: John Snow Labs +name: finetuned_bge_base_english_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BGEEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bge_base_english_pipeline` is a English model originally trained by ivanleomk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bge_base_english_pipeline_en_5.5.1_3.0_1731312760292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bge_base_english_pipeline_en_5.5.1_3.0_1731312760292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_bge_base_english_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_bge_base_english_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bge_base_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|376.1 MB| + +## References + +https://huggingface.co/ivanleomk/finetuned-bge-base-en + +## Included Models + +- DocumentAssembler +- BGEEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-finetuned_embedding_v3_en.md b/docs/_posts/ahmedlone127/2024-11-11-finetuned_embedding_v3_en.md new file mode 100644 index 00000000000000..db764750f949ff --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-finetuned_embedding_v3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English finetuned_embedding_v3 MPNetEmbeddings from KayaAI +author: John Snow Labs +name: finetuned_embedding_v3 +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_embedding_v3` is a English model originally trained by KayaAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_embedding_v3_en_5.5.1_3.0_1731294877887.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_embedding_v3_en_5.5.1_3.0_1731294877887.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") + +embeddings = MPNetEmbeddings.pretrained("finetuned_embedding_v3","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("finetuned_embedding_v3","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_embedding_v3| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/KayaAI/finetuned_embedding_v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-finetuned_embedding_v3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-finetuned_embedding_v3_pipeline_en.md new file mode 100644 index 00000000000000..f2c4c95430ccde --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-finetuned_embedding_v3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English finetuned_embedding_v3_pipeline pipeline MPNetEmbeddings from KayaAI +author: John Snow Labs +name: finetuned_embedding_v3_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_embedding_v3_pipeline` is a English model originally trained by KayaAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_embedding_v3_pipeline_en_5.5.1_3.0_1731294900663.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_embedding_v3_pipeline_en_5.5.1_3.0_1731294900663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_embedding_v3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_embedding_v3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_embedding_v3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/KayaAI/finetuned_embedding_v3 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-finetuned_sentence_similarity_en.md b/docs/_posts/ahmedlone127/2024-11-11-finetuned_sentence_similarity_en.md new file mode 100644 index 00000000000000..52d484ace9a5e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-finetuned_sentence_similarity_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English finetuned_sentence_similarity MPNetForSequenceClassification from SynthAIzer +author: John Snow Labs +name: finetuned_sentence_similarity +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentence_similarity` is a English model originally trained by SynthAIzer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentence_similarity_en_5.5.1_3.0_1731301475665.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentence_similarity_en_5.5.1_3.0_1731301475665.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 = MPNetForSequenceClassification.pretrained("finetuned_sentence_similarity","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("finetuned_sentence_similarity", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sentence_similarity| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.2 MB| + +## References + +https://huggingface.co/SynthAIzer/finetuned-sentence-similarity \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-finetuned_sentence_similarity_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-finetuned_sentence_similarity_pipeline_en.md new file mode 100644 index 00000000000000..9c2bffa5fa63ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-finetuned_sentence_similarity_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English finetuned_sentence_similarity_pipeline pipeline MPNetForSequenceClassification from SynthAIzer +author: John Snow Labs +name: finetuned_sentence_similarity_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sentence_similarity_pipeline` is a English model originally trained by SynthAIzer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sentence_similarity_pipeline_en_5.5.1_3.0_1731301497210.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sentence_similarity_pipeline_en_5.5.1_3.0_1731301497210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("finetuned_sentence_similarity_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("finetuned_sentence_similarity_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sentence_similarity_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.2 MB| + +## References + +https://huggingface.co/SynthAIzer/finetuned-sentence-similarity + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-flash_italian_ns_classifier_fpt_en.md b/docs/_posts/ahmedlone127/2024-11-11-flash_italian_ns_classifier_fpt_en.md new file mode 100644 index 00000000000000..b22987d16eea1e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-flash_italian_ns_classifier_fpt_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English flash_italian_ns_classifier_fpt BertForSequenceClassification from mrinaldi +author: John Snow Labs +name: flash_italian_ns_classifier_fpt +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flash_italian_ns_classifier_fpt` is a English model originally trained by mrinaldi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flash_italian_ns_classifier_fpt_en_5.5.1_3.0_1731310131977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flash_italian_ns_classifier_fpt_en_5.5.1_3.0_1731310131977.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("flash_italian_ns_classifier_fpt","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("flash_italian_ns_classifier_fpt", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|flash_italian_ns_classifier_fpt| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.8 MB| + +## References + +https://huggingface.co/mrinaldi/flash-it-ns-classifier-fpt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-flash_italian_ns_classifier_fpt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-flash_italian_ns_classifier_fpt_pipeline_en.md new file mode 100644 index 00000000000000..c0e1f68af987d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-flash_italian_ns_classifier_fpt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English flash_italian_ns_classifier_fpt_pipeline pipeline BertForSequenceClassification from mrinaldi +author: John Snow Labs +name: flash_italian_ns_classifier_fpt_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`flash_italian_ns_classifier_fpt_pipeline` is a English model originally trained by mrinaldi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/flash_italian_ns_classifier_fpt_pipeline_en_5.5.1_3.0_1731310156304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/flash_italian_ns_classifier_fpt_pipeline_en_5.5.1_3.0_1731310156304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("flash_italian_ns_classifier_fpt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("flash_italian_ns_classifier_fpt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|flash_italian_ns_classifier_fpt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.8 MB| + +## References + +https://huggingface.co/mrinaldi/flash-it-ns-classifier-fpt + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fund_embedder_en.md b/docs/_posts/ahmedlone127/2024-11-11-fund_embedder_en.md new file mode 100644 index 00000000000000..4abe5667d2f891 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fund_embedder_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English fund_embedder MPNetEmbeddings from tifin-india +author: John Snow Labs +name: fund_embedder +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fund_embedder` is a English model originally trained by tifin-india. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fund_embedder_en_5.5.1_3.0_1731295095363.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fund_embedder_en_5.5.1_3.0_1731295095363.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") + +embeddings = MPNetEmbeddings.pretrained("fund_embedder","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("fund_embedder","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fund_embedder| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/tifin-india/fund-embedder \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-fund_embedder_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-fund_embedder_pipeline_en.md new file mode 100644 index 00000000000000..2126840c73fb50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-fund_embedder_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English fund_embedder_pipeline pipeline MPNetEmbeddings from tifin-india +author: John Snow Labs +name: fund_embedder_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fund_embedder_pipeline` is a English model originally trained by tifin-india. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fund_embedder_pipeline_en_5.5.1_3.0_1731295128618.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fund_embedder_pipeline_en_5.5.1_3.0_1731295128618.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("fund_embedder_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("fund_embedder_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fund_embedder_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|387.1 MB| + +## References + +https://huggingface.co/tifin-india/fund-embedder + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hardware_ner_prod_en.md b/docs/_posts/ahmedlone127/2024-11-11-hardware_ner_prod_en.md new file mode 100644 index 00000000000000..87812d0d24795d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hardware_ner_prod_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hardware_ner_prod BertForTokenClassification from hadiaskari98 +author: John Snow Labs +name: hardware_ner_prod +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hardware_ner_prod` is a English model originally trained by hadiaskari98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hardware_ner_prod_en_5.5.1_3.0_1731299413030.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hardware_ner_prod_en_5.5.1_3.0_1731299413030.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') + +tokenClassifier = BertForTokenClassification.pretrained("hardware_ner_prod","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("hardware_ner_prod", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hardware_ner_prod| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/hadiaskari98/Hardware_NER_prod \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hardware_ner_prod_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-hardware_ner_prod_pipeline_en.md new file mode 100644 index 00000000000000..a1f134e615be42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hardware_ner_prod_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hardware_ner_prod_pipeline pipeline BertForTokenClassification from hadiaskari98 +author: John Snow Labs +name: hardware_ner_prod_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hardware_ner_prod_pipeline` is a English model originally trained by hadiaskari98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hardware_ner_prod_pipeline_en_5.5.1_3.0_1731299477477.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hardware_ner_prod_pipeline_en_5.5.1_3.0_1731299477477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hardware_ner_prod_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hardware_ner_prod_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hardware_ner_prod_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/hadiaskari98/Hardware_NER_prod + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hebert_finetuned_precedents_he.md b/docs/_posts/ahmedlone127/2024-11-11-hebert_finetuned_precedents_he.md new file mode 100644 index 00000000000000..5a824261538baa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hebert_finetuned_precedents_he.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Hebrew hebert_finetuned_precedents BertForQuestionAnswering from shay681 +author: John Snow Labs +name: hebert_finetuned_precedents +date: 2024-11-11 +tags: [he, open_source, onnx, question_answering, bert] +task: Question Answering +language: he +edition: Spark NLP 5.5.1 +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.`hebert_finetuned_precedents` is a Hebrew model originally trained by shay681. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hebert_finetuned_precedents_he_5.5.1_3.0_1731307828918.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hebert_finetuned_precedents_he_5.5.1_3.0_1731307828918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("hebert_finetuned_precedents","he") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("hebert_finetuned_precedents", "he") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hebert_finetuned_precedents| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|he| +|Size:|408.1 MB| + +## References + +https://huggingface.co/shay681/HeBERT_finetuned_Precedents \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hebert_finetuned_precedents_pipeline_he.md b/docs/_posts/ahmedlone127/2024-11-11-hebert_finetuned_precedents_pipeline_he.md new file mode 100644 index 00000000000000..c4699032f5ebb6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hebert_finetuned_precedents_pipeline_he.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Hebrew hebert_finetuned_precedents_pipeline pipeline BertForQuestionAnswering from shay681 +author: John Snow Labs +name: hebert_finetuned_precedents_pipeline +date: 2024-11-11 +tags: [he, open_source, pipeline, onnx] +task: Question Answering +language: he +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hebert_finetuned_precedents_pipeline` is a Hebrew model originally trained by shay681. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hebert_finetuned_precedents_pipeline_he_5.5.1_3.0_1731307850161.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hebert_finetuned_precedents_pipeline_he_5.5.1_3.0_1731307850161.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hebert_finetuned_precedents_pipeline", lang = "he") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hebert_finetuned_precedents_pipeline", lang = "he") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hebert_finetuned_precedents_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|he| +|Size:|408.1 MB| + +## References + +https://huggingface.co/shay681/HeBERT_finetuned_Precedents + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hs_arabic_translate_syn_4class_for_tool_en.md b/docs/_posts/ahmedlone127/2024-11-11-hs_arabic_translate_syn_4class_for_tool_en.md new file mode 100644 index 00000000000000..83ca6f6b20b0a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hs_arabic_translate_syn_4class_for_tool_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English hs_arabic_translate_syn_4class_for_tool BertForSequenceClassification from SoDehghan +author: John Snow Labs +name: hs_arabic_translate_syn_4class_for_tool +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hs_arabic_translate_syn_4class_for_tool` is a English model originally trained by SoDehghan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hs_arabic_translate_syn_4class_for_tool_en_5.5.1_3.0_1731309364917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hs_arabic_translate_syn_4class_for_tool_en_5.5.1_3.0_1731309364917.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("hs_arabic_translate_syn_4class_for_tool","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hs_arabic_translate_syn_4class_for_tool", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hs_arabic_translate_syn_4class_for_tool| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.5 MB| + +## References + +https://huggingface.co/SoDehghan/hs-ar-translate-syn-4class-for-tool \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hs_arabic_translate_syn_4class_for_tool_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-hs_arabic_translate_syn_4class_for_tool_pipeline_en.md new file mode 100644 index 00000000000000..0e5028da215122 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hs_arabic_translate_syn_4class_for_tool_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English hs_arabic_translate_syn_4class_for_tool_pipeline pipeline BertForSequenceClassification from SoDehghan +author: John Snow Labs +name: hs_arabic_translate_syn_4class_for_tool_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hs_arabic_translate_syn_4class_for_tool_pipeline` is a English model originally trained by SoDehghan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hs_arabic_translate_syn_4class_for_tool_pipeline_en_5.5.1_3.0_1731309392366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hs_arabic_translate_syn_4class_for_tool_pipeline_en_5.5.1_3.0_1731309392366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hs_arabic_translate_syn_4class_for_tool_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hs_arabic_translate_syn_4class_for_tool_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hs_arabic_translate_syn_4class_for_tool_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|507.5 MB| + +## References + +https://huggingface.co/SoDehghan/hs-ar-translate-syn-4class-for-tool + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hubert_base_japanese_asr_ja.md b/docs/_posts/ahmedlone127/2024-11-11-hubert_base_japanese_asr_ja.md new file mode 100644 index 00000000000000..9664aa5c122e38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hubert_base_japanese_asr_ja.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Japanese hubert_base_japanese_asr HubertForCTC from TKU410410103 +author: John Snow Labs +name: hubert_base_japanese_asr +date: 2024-11-11 +tags: [ja, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_base_japanese_asr` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_base_japanese_asr_ja_5.5.1_3.0_1731284393140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_base_japanese_asr_ja_5.5.1_3.0_1731284393140.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 = HubertForCTC.pretrained("hubert_base_japanese_asr","ja") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("hubert_base_japanese_asr", "ja") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_base_japanese_asr| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ja| +|Size:|697.4 MB| + +## References + +https://huggingface.co/TKU410410103/hubert-base-japanese-asr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hubert_base_japanese_asr_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-11-11-hubert_base_japanese_asr_pipeline_ja.md new file mode 100644 index 00000000000000..a3c5ebae6a180f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hubert_base_japanese_asr_pipeline_ja.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Japanese hubert_base_japanese_asr_pipeline pipeline HubertForCTC from TKU410410103 +author: John Snow Labs +name: hubert_base_japanese_asr_pipeline +date: 2024-11-11 +tags: [ja, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_base_japanese_asr_pipeline` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_base_japanese_asr_pipeline_ja_5.5.1_3.0_1731284434411.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_base_japanese_asr_pipeline_ja_5.5.1_3.0_1731284434411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hubert_base_japanese_asr_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hubert_base_japanese_asr_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_base_japanese_asr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|697.4 MB| + +## References + +https://huggingface.co/TKU410410103/hubert-base-japanese-asr + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hubert_large_arabic_egyptian_ar.md b/docs/_posts/ahmedlone127/2024-11-11-hubert_large_arabic_egyptian_ar.md new file mode 100644 index 00000000000000..7efe6d4c7e1243 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hubert_large_arabic_egyptian_ar.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Arabic hubert_large_arabic_egyptian HubertForCTC from omarxadel +author: John Snow Labs +name: hubert_large_arabic_egyptian +date: 2024-11-11 +tags: [ar, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: ar +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_large_arabic_egyptian` is a Arabic model originally trained by omarxadel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_large_arabic_egyptian_ar_5.5.1_3.0_1731283621734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_large_arabic_egyptian_ar_5.5.1_3.0_1731283621734.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 = HubertForCTC.pretrained("hubert_large_arabic_egyptian","ar") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("hubert_large_arabic_egyptian", "ar") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_large_arabic_egyptian| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ar| +|Size:|2.4 GB| + +## References + +https://huggingface.co/omarxadel/hubert-large-arabic-egyptian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hubert_large_arabic_egyptian_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-11-11-hubert_large_arabic_egyptian_pipeline_ar.md new file mode 100644 index 00000000000000..be4886ef62da41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hubert_large_arabic_egyptian_pipeline_ar.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Arabic hubert_large_arabic_egyptian_pipeline pipeline HubertForCTC from omarxadel +author: John Snow Labs +name: hubert_large_arabic_egyptian_pipeline +date: 2024-11-11 +tags: [ar, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ar +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_large_arabic_egyptian_pipeline` is a Arabic model originally trained by omarxadel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_large_arabic_egyptian_pipeline_ar_5.5.1_3.0_1731283742320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_large_arabic_egyptian_pipeline_ar_5.5.1_3.0_1731283742320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hubert_large_arabic_egyptian_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hubert_large_arabic_egyptian_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_large_arabic_egyptian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|2.4 GB| + +## References + +https://huggingface.co/omarxadel/hubert-large-arabic-egyptian + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hubert_large_japanese_asr_ja.md b/docs/_posts/ahmedlone127/2024-11-11-hubert_large_japanese_asr_ja.md new file mode 100644 index 00000000000000..fc3dc746222497 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hubert_large_japanese_asr_ja.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Japanese hubert_large_japanese_asr HubertForCTC from TKU410410103 +author: John Snow Labs +name: hubert_large_japanese_asr +date: 2024-11-11 +tags: [ja, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_large_japanese_asr` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_large_japanese_asr_ja_5.5.1_3.0_1731283708086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_large_japanese_asr_ja_5.5.1_3.0_1731283708086.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 = HubertForCTC.pretrained("hubert_large_japanese_asr","ja") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("hubert_large_japanese_asr", "ja") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_large_japanese_asr| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ja| +|Size:|2.4 GB| + +## References + +https://huggingface.co/TKU410410103/hubert-large-japanese-asr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hubert_large_japanese_asr_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-11-11-hubert_large_japanese_asr_pipeline_ja.md new file mode 100644 index 00000000000000..6259a5600a7c6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hubert_large_japanese_asr_pipeline_ja.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Japanese hubert_large_japanese_asr_pipeline pipeline HubertForCTC from TKU410410103 +author: John Snow Labs +name: hubert_large_japanese_asr_pipeline +date: 2024-11-11 +tags: [ja, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_large_japanese_asr_pipeline` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_large_japanese_asr_pipeline_ja_5.5.1_3.0_1731283833877.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_large_japanese_asr_pipeline_ja_5.5.1_3.0_1731283833877.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hubert_large_japanese_asr_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hubert_large_japanese_asr_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_large_japanese_asr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|2.4 GB| + +## References + +https://huggingface.co/TKU410410103/hubert-large-japanese-asr + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hubert_ukrainian_pipeline_uk.md b/docs/_posts/ahmedlone127/2024-11-11-hubert_ukrainian_pipeline_uk.md new file mode 100644 index 00000000000000..b0f3f201db86bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hubert_ukrainian_pipeline_uk.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Ukrainian hubert_ukrainian_pipeline pipeline HubertForCTC from Yehor +author: John Snow Labs +name: hubert_ukrainian_pipeline +date: 2024-11-11 +tags: [uk, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: uk +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_ukrainian_pipeline` is a Ukrainian model originally trained by Yehor. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_ukrainian_pipeline_uk_5.5.1_3.0_1731284523933.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_ukrainian_pipeline_uk_5.5.1_3.0_1731284523933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hubert_ukrainian_pipeline", lang = "uk") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hubert_ukrainian_pipeline", lang = "uk") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_ukrainian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|uk| +|Size:|708.6 MB| + +## References + +https://huggingface.co/Yehor/hubert-uk + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hubert_ukrainian_uk.md b/docs/_posts/ahmedlone127/2024-11-11-hubert_ukrainian_uk.md new file mode 100644 index 00000000000000..6e6498989a4c9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hubert_ukrainian_uk.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Ukrainian hubert_ukrainian HubertForCTC from Yehor +author: John Snow Labs +name: hubert_ukrainian +date: 2024-11-11 +tags: [uk, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: uk +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hubert_ukrainian` is a Ukrainian model originally trained by Yehor. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hubert_ukrainian_uk_5.5.1_3.0_1731284486012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hubert_ukrainian_uk_5.5.1_3.0_1731284486012.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 = HubertForCTC.pretrained("hubert_ukrainian","uk") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("hubert_ukrainian", "uk") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hubert_ukrainian| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|uk| +|Size:|708.6 MB| + +## References + +https://huggingface.co/Yehor/hubert-uk \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hw1_2_question_answering_bert_base_chinese_finetuned_en.md b/docs/_posts/ahmedlone127/2024-11-11-hw1_2_question_answering_bert_base_chinese_finetuned_en.md new file mode 100644 index 00000000000000..78f9ba44376001 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hw1_2_question_answering_bert_base_chinese_finetuned_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English hw1_2_question_answering_bert_base_chinese_finetuned BertForQuestionAnswering from b10401015 +author: John Snow Labs +name: hw1_2_question_answering_bert_base_chinese_finetuned +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`hw1_2_question_answering_bert_base_chinese_finetuned` is a English model originally trained by b10401015. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_2_question_answering_bert_base_chinese_finetuned_en_5.5.1_3.0_1731289448071.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_2_question_answering_bert_base_chinese_finetuned_en_5.5.1_3.0_1731289448071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("hw1_2_question_answering_bert_base_chinese_finetuned","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("hw1_2_question_answering_bert_base_chinese_finetuned", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hw1_2_question_answering_bert_base_chinese_finetuned| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|381.1 MB| + +## References + +https://huggingface.co/b10401015/hw1-2-question_answering-bert-base-chinese-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-hw1_2_question_answering_bert_base_chinese_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-hw1_2_question_answering_bert_base_chinese_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..27192cee5c112e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-hw1_2_question_answering_bert_base_chinese_finetuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English hw1_2_question_answering_bert_base_chinese_finetuned_pipeline pipeline BertForQuestionAnswering from b10401015 +author: John Snow Labs +name: hw1_2_question_answering_bert_base_chinese_finetuned_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hw1_2_question_answering_bert_base_chinese_finetuned_pipeline` is a English model originally trained by b10401015. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hw1_2_question_answering_bert_base_chinese_finetuned_pipeline_en_5.5.1_3.0_1731289468089.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hw1_2_question_answering_bert_base_chinese_finetuned_pipeline_en_5.5.1_3.0_1731289468089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("hw1_2_question_answering_bert_base_chinese_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("hw1_2_question_answering_bert_base_chinese_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hw1_2_question_answering_bert_base_chinese_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|381.1 MB| + +## References + +https://huggingface.co/b10401015/hw1-2-question_answering-bert-base-chinese-finetuned + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-indobert_squad_indonesian_en.md b/docs/_posts/ahmedlone127/2024-11-11-indobert_squad_indonesian_en.md new file mode 100644 index 00000000000000..83f7c5bb4fd845 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-indobert_squad_indonesian_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English indobert_squad_indonesian BertForQuestionAnswering from malaputri +author: John Snow Labs +name: indobert_squad_indonesian +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`indobert_squad_indonesian` is a English model originally trained by malaputri. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_squad_indonesian_en_5.5.1_3.0_1731288942482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_squad_indonesian_en_5.5.1_3.0_1731288942482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("indobert_squad_indonesian","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("indobert_squad_indonesian", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_squad_indonesian| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.2 MB| + +## References + +https://huggingface.co/malaputri/indobert-squad-id \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-indobert_squad_indonesian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-indobert_squad_indonesian_pipeline_en.md new file mode 100644 index 00000000000000..0e68cf8f231ab5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-indobert_squad_indonesian_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English indobert_squad_indonesian_pipeline pipeline BertForQuestionAnswering from malaputri +author: John Snow Labs +name: indobert_squad_indonesian_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobert_squad_indonesian_pipeline` is a English model originally trained by malaputri. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobert_squad_indonesian_pipeline_en_5.5.1_3.0_1731288966242.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobert_squad_indonesian_pipeline_en_5.5.1_3.0_1731288966242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indobert_squad_indonesian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indobert_squad_indonesian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobert_squad_indonesian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.2 MB| + +## References + +https://huggingface.co/malaputri/indobert-squad-id + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-indonesian_roberta_base_nerp_tagger_en.md b/docs/_posts/ahmedlone127/2024-11-11-indonesian_roberta_base_nerp_tagger_en.md new file mode 100644 index 00000000000000..20ab05f1228396 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-indonesian_roberta_base_nerp_tagger_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English indonesian_roberta_base_nerp_tagger RoBertaForTokenClassification from w11wo +author: John Snow Labs +name: indonesian_roberta_base_nerp_tagger +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_roberta_base_nerp_tagger` is a English model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_roberta_base_nerp_tagger_en_5.5.1_3.0_1731311367416.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_roberta_base_nerp_tagger_en_5.5.1_3.0_1731311367416.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("indonesian_roberta_base_nerp_tagger","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("indonesian_roberta_base_nerp_tagger", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_roberta_base_nerp_tagger| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|465.5 MB| + +## References + +https://huggingface.co/w11wo/indonesian-roberta-base-nerp-tagger \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-indonesian_roberta_base_nerp_tagger_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-indonesian_roberta_base_nerp_tagger_pipeline_en.md new file mode 100644 index 00000000000000..ed62781eb46655 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-indonesian_roberta_base_nerp_tagger_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English indonesian_roberta_base_nerp_tagger_pipeline pipeline RoBertaForTokenClassification from w11wo +author: John Snow Labs +name: indonesian_roberta_base_nerp_tagger_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indonesian_roberta_base_nerp_tagger_pipeline` is a English model originally trained by w11wo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indonesian_roberta_base_nerp_tagger_pipeline_en_5.5.1_3.0_1731311391967.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indonesian_roberta_base_nerp_tagger_pipeline_en_5.5.1_3.0_1731311391967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("indonesian_roberta_base_nerp_tagger_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("indonesian_roberta_base_nerp_tagger_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indonesian_roberta_base_nerp_tagger_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.5 MB| + +## References + +https://huggingface.co/w11wo/indonesian-roberta-base-nerp-tagger + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-kaggle_detect_generated_text_en.md b/docs/_posts/ahmedlone127/2024-11-11-kaggle_detect_generated_text_en.md new file mode 100644 index 00000000000000..eac97868008a6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-kaggle_detect_generated_text_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English kaggle_detect_generated_text BertForSequenceClassification from fagner +author: John Snow Labs +name: kaggle_detect_generated_text +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kaggle_detect_generated_text` is a English model originally trained by fagner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kaggle_detect_generated_text_en_5.5.1_3.0_1731309407438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kaggle_detect_generated_text_en_5.5.1_3.0_1731309407438.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("kaggle_detect_generated_text","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("kaggle_detect_generated_text", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kaggle_detect_generated_text| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/fagner/kaggle-detect-generated-text \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-kaggle_detect_generated_text_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-kaggle_detect_generated_text_pipeline_en.md new file mode 100644 index 00000000000000..bc1c2e832b4942 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-kaggle_detect_generated_text_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English kaggle_detect_generated_text_pipeline pipeline BertForSequenceClassification from fagner +author: John Snow Labs +name: kaggle_detect_generated_text_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kaggle_detect_generated_text_pipeline` is a English model originally trained by fagner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kaggle_detect_generated_text_pipeline_en_5.5.1_3.0_1731309428785.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kaggle_detect_generated_text_pipeline_en_5.5.1_3.0_1731309428785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("kaggle_detect_generated_text_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("kaggle_detect_generated_text_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kaggle_detect_generated_text_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/fagner/kaggle-detect-generated-text + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-keybert_bulgarian_bg.md b/docs/_posts/ahmedlone127/2024-11-11-keybert_bulgarian_bg.md new file mode 100644 index 00000000000000..b2cfa011512d1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-keybert_bulgarian_bg.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Bulgarian keybert_bulgarian BertForTokenClassification from auhide +author: John Snow Labs +name: keybert_bulgarian +date: 2024-11-11 +tags: [bg, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: bg +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keybert_bulgarian` is a Bulgarian model originally trained by auhide. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keybert_bulgarian_bg_5.5.1_3.0_1731299301822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keybert_bulgarian_bg_5.5.1_3.0_1731299301822.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') + +tokenClassifier = BertForTokenClassification.pretrained("keybert_bulgarian","bg") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("keybert_bulgarian", "bg") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|keybert_bulgarian| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|bg| +|Size:|665.0 MB| + +## References + +https://huggingface.co/auhide/keybert-bg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-keybert_bulgarian_pipeline_bg.md b/docs/_posts/ahmedlone127/2024-11-11-keybert_bulgarian_pipeline_bg.md new file mode 100644 index 00000000000000..9949e29c23a12b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-keybert_bulgarian_pipeline_bg.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Bulgarian keybert_bulgarian_pipeline pipeline BertForTokenClassification from auhide +author: John Snow Labs +name: keybert_bulgarian_pipeline +date: 2024-11-11 +tags: [bg, open_source, pipeline, onnx] +task: Named Entity Recognition +language: bg +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`keybert_bulgarian_pipeline` is a Bulgarian model originally trained by auhide. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/keybert_bulgarian_pipeline_bg_5.5.1_3.0_1731299335640.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/keybert_bulgarian_pipeline_bg_5.5.1_3.0_1731299335640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("keybert_bulgarian_pipeline", lang = "bg") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("keybert_bulgarian_pipeline", lang = "bg") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|keybert_bulgarian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|bg| +|Size:|665.1 MB| + +## References + +https://huggingface.co/auhide/keybert-bg + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-kor_naver_ner_name_v2_en.md b/docs/_posts/ahmedlone127/2024-11-11-kor_naver_ner_name_v2_en.md new file mode 100644 index 00000000000000..40a7461b0e818f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-kor_naver_ner_name_v2_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English kor_naver_ner_name_v2 BertForTokenClassification from joon09 +author: John Snow Labs +name: kor_naver_ner_name_v2 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kor_naver_ner_name_v2` is a English model originally trained by joon09. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kor_naver_ner_name_v2_en_5.5.1_3.0_1731291030118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kor_naver_ner_name_v2_en_5.5.1_3.0_1731291030118.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') + +tokenClassifier = BertForTokenClassification.pretrained("kor_naver_ner_name_v2","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("kor_naver_ner_name_v2", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kor_naver_ner_name_v2| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|441.2 MB| + +## References + +https://huggingface.co/joon09/kor-naver-ner-name-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-kor_naver_ner_name_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-kor_naver_ner_name_v2_pipeline_en.md new file mode 100644 index 00000000000000..7d1d6374b024e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-kor_naver_ner_name_v2_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English kor_naver_ner_name_v2_pipeline pipeline BertForTokenClassification from joon09 +author: John Snow Labs +name: kor_naver_ner_name_v2_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kor_naver_ner_name_v2_pipeline` is a English model originally trained by joon09. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kor_naver_ner_name_v2_pipeline_en_5.5.1_3.0_1731291052670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kor_naver_ner_name_v2_pipeline_en_5.5.1_3.0_1731291052670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("kor_naver_ner_name_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("kor_naver_ner_name_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kor_naver_ner_name_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|441.3 MB| + +## References + +https://huggingface.co/joon09/kor-naver-ner-name-v2 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-legal_gqa_7_bert_augmented_all_1000_en.md b/docs/_posts/ahmedlone127/2024-11-11-legal_gqa_7_bert_augmented_all_1000_en.md new file mode 100644 index 00000000000000..93178bb39d4a64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-legal_gqa_7_bert_augmented_all_1000_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English legal_gqa_7_bert_augmented_all_1000 BertForQuestionAnswering from farid1088 +author: John Snow Labs +name: legal_gqa_7_bert_augmented_all_1000 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`legal_gqa_7_bert_augmented_all_1000` is a English model originally trained by farid1088. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_gqa_7_bert_augmented_all_1000_en_5.5.1_3.0_1731289218328.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_gqa_7_bert_augmented_all_1000_en_5.5.1_3.0_1731289218328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("legal_gqa_7_bert_augmented_all_1000","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("legal_gqa_7_bert_augmented_all_1000", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_gqa_7_bert_augmented_all_1000| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/farid1088/Legal_GQA_7_BERT_augmented_all_1000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-legal_gqa_7_bert_augmented_all_1000_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-legal_gqa_7_bert_augmented_all_1000_pipeline_en.md new file mode 100644 index 00000000000000..9c0b67bc6ada0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-legal_gqa_7_bert_augmented_all_1000_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English legal_gqa_7_bert_augmented_all_1000_pipeline pipeline BertForQuestionAnswering from farid1088 +author: John Snow Labs +name: legal_gqa_7_bert_augmented_all_1000_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_gqa_7_bert_augmented_all_1000_pipeline` is a English model originally trained by farid1088. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_gqa_7_bert_augmented_all_1000_pipeline_en_5.5.1_3.0_1731289252285.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_gqa_7_bert_augmented_all_1000_pipeline_en_5.5.1_3.0_1731289252285.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("legal_gqa_7_bert_augmented_all_1000_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("legal_gqa_7_bert_augmented_all_1000_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_gqa_7_bert_augmented_all_1000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/farid1088/Legal_GQA_7_BERT_augmented_all_1000 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-lettuce_sayula_popoluca_dutch_mono_en.md b/docs/_posts/ahmedlone127/2024-11-11-lettuce_sayula_popoluca_dutch_mono_en.md new file mode 100644 index 00000000000000..ff6f51c90581f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-lettuce_sayula_popoluca_dutch_mono_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English lettuce_sayula_popoluca_dutch_mono RoBertaForTokenClassification from pranaydeeps +author: John Snow Labs +name: lettuce_sayula_popoluca_dutch_mono +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lettuce_sayula_popoluca_dutch_mono` is a English model originally trained by pranaydeeps. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_dutch_mono_en_5.5.1_3.0_1731314245313.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_dutch_mono_en_5.5.1_3.0_1731314245313.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("lettuce_sayula_popoluca_dutch_mono","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("lettuce_sayula_popoluca_dutch_mono", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lettuce_sayula_popoluca_dutch_mono| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|436.2 MB| + +## References + +https://huggingface.co/pranaydeeps/lettuce_pos_nl_mono \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-lettuce_sayula_popoluca_dutch_mono_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-lettuce_sayula_popoluca_dutch_mono_pipeline_en.md new file mode 100644 index 00000000000000..30c2a8037a1fce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-lettuce_sayula_popoluca_dutch_mono_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English lettuce_sayula_popoluca_dutch_mono_pipeline pipeline RoBertaForTokenClassification from pranaydeeps +author: John Snow Labs +name: lettuce_sayula_popoluca_dutch_mono_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`lettuce_sayula_popoluca_dutch_mono_pipeline` is a English model originally trained by pranaydeeps. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_dutch_mono_pipeline_en_5.5.1_3.0_1731314271572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/lettuce_sayula_popoluca_dutch_mono_pipeline_en_5.5.1_3.0_1731314271572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("lettuce_sayula_popoluca_dutch_mono_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("lettuce_sayula_popoluca_dutch_mono_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|lettuce_sayula_popoluca_dutch_mono_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|436.2 MB| + +## References + +https://huggingface.co/pranaydeeps/lettuce_pos_nl_mono + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-linshoufanfork_whisper_small_nan_twi_pinyin_en.md b/docs/_posts/ahmedlone127/2024-11-11-linshoufanfork_whisper_small_nan_twi_pinyin_en.md new file mode 100644 index 00000000000000..c49affe661f3d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-linshoufanfork_whisper_small_nan_twi_pinyin_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English linshoufanfork_whisper_small_nan_twi_pinyin WhisperForCTC from linshoufan +author: John Snow Labs +name: linshoufanfork_whisper_small_nan_twi_pinyin +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`linshoufanfork_whisper_small_nan_twi_pinyin` is a English model originally trained by linshoufan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/linshoufanfork_whisper_small_nan_twi_pinyin_en_5.5.1_3.0_1731302380184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/linshoufanfork_whisper_small_nan_twi_pinyin_en_5.5.1_3.0_1731302380184.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("linshoufanfork_whisper_small_nan_twi_pinyin","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("linshoufanfork_whisper_small_nan_twi_pinyin", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|linshoufanfork_whisper_small_nan_twi_pinyin| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/linshoufan/linshoufanfork-whisper-small-nan-tw-pinyin \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-linshoufanfork_whisper_small_nan_twi_pinyin_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-linshoufanfork_whisper_small_nan_twi_pinyin_pipeline_en.md new file mode 100644 index 00000000000000..b2662dfecf5220 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-linshoufanfork_whisper_small_nan_twi_pinyin_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English linshoufanfork_whisper_small_nan_twi_pinyin_pipeline pipeline WhisperForCTC from linshoufan +author: John Snow Labs +name: linshoufanfork_whisper_small_nan_twi_pinyin_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`linshoufanfork_whisper_small_nan_twi_pinyin_pipeline` is a English model originally trained by linshoufan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/linshoufanfork_whisper_small_nan_twi_pinyin_pipeline_en_5.5.1_3.0_1731302466551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/linshoufanfork_whisper_small_nan_twi_pinyin_pipeline_en_5.5.1_3.0_1731302466551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("linshoufanfork_whisper_small_nan_twi_pinyin_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("linshoufanfork_whisper_small_nan_twi_pinyin_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|linshoufanfork_whisper_small_nan_twi_pinyin_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/linshoufan/linshoufanfork-whisper-small-nan-tw-pinyin + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-malaysian_whisper_tiny_ms.md b/docs/_posts/ahmedlone127/2024-11-11-malaysian_whisper_tiny_ms.md new file mode 100644 index 00000000000000..d5635f50e1d8cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-malaysian_whisper_tiny_ms.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Malay (macrolanguage) malaysian_whisper_tiny WhisperForCTC from mesolitica +author: John Snow Labs +name: malaysian_whisper_tiny +date: 2024-11-11 +tags: [ms, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: ms +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`malaysian_whisper_tiny` is a Malay (macrolanguage) model originally trained by mesolitica. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malaysian_whisper_tiny_ms_5.5.1_3.0_1731305964206.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malaysian_whisper_tiny_ms_5.5.1_3.0_1731305964206.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("malaysian_whisper_tiny","ms") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("malaysian_whisper_tiny", "ms") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|malaysian_whisper_tiny| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ms| +|Size:|191.1 MB| + +## References + +https://huggingface.co/mesolitica/malaysian-whisper-tiny \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-malaysian_whisper_tiny_pipeline_ms.md b/docs/_posts/ahmedlone127/2024-11-11-malaysian_whisper_tiny_pipeline_ms.md new file mode 100644 index 00000000000000..68a49271f19872 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-malaysian_whisper_tiny_pipeline_ms.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Malay (macrolanguage) malaysian_whisper_tiny_pipeline pipeline WhisperForCTC from mesolitica +author: John Snow Labs +name: malaysian_whisper_tiny_pipeline +date: 2024-11-11 +tags: [ms, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ms +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`malaysian_whisper_tiny_pipeline` is a Malay (macrolanguage) model originally trained by mesolitica. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/malaysian_whisper_tiny_pipeline_ms_5.5.1_3.0_1731306024102.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/malaysian_whisper_tiny_pipeline_ms_5.5.1_3.0_1731306024102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("malaysian_whisper_tiny_pipeline", lang = "ms") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("malaysian_whisper_tiny_pipeline", lang = "ms") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|malaysian_whisper_tiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ms| +|Size:|191.1 MB| + +## References + +https://huggingface.co/mesolitica/malaysian-whisper-tiny + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mbert_finetuned_mlqa_dev_spanish_chinese_hindi_en.md b/docs/_posts/ahmedlone127/2024-11-11-mbert_finetuned_mlqa_dev_spanish_chinese_hindi_en.md new file mode 100644 index 00000000000000..a24fea30c337a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mbert_finetuned_mlqa_dev_spanish_chinese_hindi_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mbert_finetuned_mlqa_dev_spanish_chinese_hindi BertForQuestionAnswering from roshnir +author: John Snow Labs +name: mbert_finetuned_mlqa_dev_spanish_chinese_hindi +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`mbert_finetuned_mlqa_dev_spanish_chinese_hindi` is a English model originally trained by roshnir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_finetuned_mlqa_dev_spanish_chinese_hindi_en_5.5.1_3.0_1731308064944.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_finetuned_mlqa_dev_spanish_chinese_hindi_en_5.5.1_3.0_1731308064944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("mbert_finetuned_mlqa_dev_spanish_chinese_hindi","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("mbert_finetuned_mlqa_dev_spanish_chinese_hindi", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbert_finetuned_mlqa_dev_spanish_chinese_hindi| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|625.5 MB| + +## References + +https://huggingface.co/roshnir/mBert-finetuned-mlqa-dev-es-zh-hi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline_en.md new file mode 100644 index 00000000000000..092368edd847aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline pipeline BertForQuestionAnswering from roshnir +author: John Snow Labs +name: mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline` is a English model originally trained by roshnir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline_en_5.5.1_3.0_1731308096792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline_en_5.5.1_3.0_1731308096792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbert_finetuned_mlqa_dev_spanish_chinese_hindi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|625.5 MB| + +## References + +https://huggingface.co/roshnir/mBert-finetuned-mlqa-dev-es-zh-hi + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mbert_urdu_en.md b/docs/_posts/ahmedlone127/2024-11-11-mbert_urdu_en.md new file mode 100644 index 00000000000000..daca24f181aa89 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mbert_urdu_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mbert_urdu BertForTokenClassification from anwesham +author: John Snow Labs +name: mbert_urdu +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_urdu` is a English model originally trained by anwesham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_urdu_en_5.5.1_3.0_1731285721176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_urdu_en_5.5.1_3.0_1731285721176.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') + +tokenClassifier = BertForTokenClassification.pretrained("mbert_urdu","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("mbert_urdu", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbert_urdu| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/anwesham/mbert_ur \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mbert_urdu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-mbert_urdu_pipeline_en.md new file mode 100644 index 00000000000000..eea33b8a7387db --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mbert_urdu_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mbert_urdu_pipeline pipeline BertForTokenClassification from anwesham +author: John Snow Labs +name: mbert_urdu_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_urdu_pipeline` is a English model originally trained by anwesham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_urdu_pipeline_en_5.5.1_3.0_1731285756767.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_urdu_pipeline_en_5.5.1_3.0_1731285756767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mbert_urdu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mbert_urdu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbert_urdu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/anwesham/mbert_ur + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-med_drugs_extraction_b_en.md b/docs/_posts/ahmedlone127/2024-11-11-med_drugs_extraction_b_en.md new file mode 100644 index 00000000000000..a410af14a15ad0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-med_drugs_extraction_b_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English med_drugs_extraction_b BertForQuestionAnswering from iliyararupzhanov +author: John Snow Labs +name: med_drugs_extraction_b +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`med_drugs_extraction_b` is a English model originally trained by iliyararupzhanov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med_drugs_extraction_b_en_5.5.1_3.0_1731289511976.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_drugs_extraction_b_en_5.5.1_3.0_1731289511976.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("med_drugs_extraction_b","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("med_drugs_extraction_b", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|med_drugs_extraction_b| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|664.3 MB| + +## References + +https://huggingface.co/iliyararupzhanov/med-drugs-extraction-b \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-med_drugs_extraction_b_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-med_drugs_extraction_b_pipeline_en.md new file mode 100644 index 00000000000000..b213293f6bfc73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-med_drugs_extraction_b_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English med_drugs_extraction_b_pipeline pipeline BertForQuestionAnswering from iliyararupzhanov +author: John Snow Labs +name: med_drugs_extraction_b_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`med_drugs_extraction_b_pipeline` is a English model originally trained by iliyararupzhanov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/med_drugs_extraction_b_pipeline_en_5.5.1_3.0_1731289549276.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/med_drugs_extraction_b_pipeline_en_5.5.1_3.0_1731289549276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("med_drugs_extraction_b_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("med_drugs_extraction_b_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|med_drugs_extraction_b_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|664.3 MB| + +## References + +https://huggingface.co/iliyararupzhanov/med-drugs-extraction-b + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-men_tshirt_en.md b/docs/_posts/ahmedlone127/2024-11-11-men_tshirt_en.md new file mode 100644 index 00000000000000..a6ed40de416d2a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-men_tshirt_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English men_tshirt CLIPForZeroShotClassification from HarshN-0722 +author: John Snow Labs +name: men_tshirt +date: 2024-11-11 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`men_tshirt` is a English model originally trained by HarshN-0722. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/men_tshirt_en_5.5.1_3.0_1731287421873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/men_tshirt_en_5.5.1_3.0_1731287421873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("men_tshirt","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("men_tshirt","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|men_tshirt| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/HarshN-0722/men-tshirt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-men_tshirt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-men_tshirt_pipeline_en.md new file mode 100644 index 00000000000000..8962b560cf8538 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-men_tshirt_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English men_tshirt_pipeline pipeline CLIPForZeroShotClassification from HarshN-0722 +author: John Snow Labs +name: men_tshirt_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`men_tshirt_pipeline` is a English model originally trained by HarshN-0722. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/men_tshirt_pipeline_en_5.5.1_3.0_1731287450972.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/men_tshirt_pipeline_en_5.5.1_3.0_1731287450972.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("men_tshirt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("men_tshirt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|men_tshirt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.3 MB| + +## References + +https://huggingface.co/HarshN-0722/men-tshirt + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mi_chatbotv3_en.md b/docs/_posts/ahmedlone127/2024-11-11-mi_chatbotv3_en.md new file mode 100644 index 00000000000000..18d56dc54176f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mi_chatbotv3_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mi_chatbotv3 BertForQuestionAnswering from DanielAvelar09 +author: John Snow Labs +name: mi_chatbotv3 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`mi_chatbotv3` is a English model originally trained by DanielAvelar09. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mi_chatbotv3_en_5.5.1_3.0_1731307787887.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mi_chatbotv3_en_5.5.1_3.0_1731307787887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("mi_chatbotv3","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("mi_chatbotv3", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mi_chatbotv3| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/DanielAvelar09/mi_chatbotV3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mi_chatbotv3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-mi_chatbotv3_pipeline_en.md new file mode 100644 index 00000000000000..26d886362fb586 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mi_chatbotv3_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mi_chatbotv3_pipeline pipeline BertForQuestionAnswering from DanielAvelar09 +author: John Snow Labs +name: mi_chatbotv3_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mi_chatbotv3_pipeline` is a English model originally trained by DanielAvelar09. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mi_chatbotv3_pipeline_en_5.5.1_3.0_1731307810155.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mi_chatbotv3_pipeline_en_5.5.1_3.0_1731307810155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mi_chatbotv3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mi_chatbotv3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mi_chatbotv3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/DanielAvelar09/mi_chatbotV3 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mobilebert_uncased_squad_v2_finetuned_en.md b/docs/_posts/ahmedlone127/2024-11-11-mobilebert_uncased_squad_v2_finetuned_en.md new file mode 100644 index 00000000000000..4d6769c4aab15c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mobilebert_uncased_squad_v2_finetuned_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mobilebert_uncased_squad_v2_finetuned BertForQuestionAnswering from badokorach +author: John Snow Labs +name: mobilebert_uncased_squad_v2_finetuned +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`mobilebert_uncased_squad_v2_finetuned` is a English model originally trained by badokorach. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v2_finetuned_en_5.5.1_3.0_1731289026811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v2_finetuned_en_5.5.1_3.0_1731289026811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("mobilebert_uncased_squad_v2_finetuned","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("mobilebert_uncased_squad_v2_finetuned", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mobilebert_uncased_squad_v2_finetuned| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|92.5 MB| + +## References + +https://huggingface.co/badokorach/mobilebert-uncased-squad-v2-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mobilebert_uncased_squad_v2_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-mobilebert_uncased_squad_v2_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..8508a5a42095a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mobilebert_uncased_squad_v2_finetuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mobilebert_uncased_squad_v2_finetuned_pipeline pipeline BertForQuestionAnswering from badokorach +author: John Snow Labs +name: mobilebert_uncased_squad_v2_finetuned_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mobilebert_uncased_squad_v2_finetuned_pipeline` is a English model originally trained by badokorach. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v2_finetuned_pipeline_en_5.5.1_3.0_1731289031710.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mobilebert_uncased_squad_v2_finetuned_pipeline_en_5.5.1_3.0_1731289031710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mobilebert_uncased_squad_v2_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mobilebert_uncased_squad_v2_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mobilebert_uncased_squad_v2_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|92.5 MB| + +## References + +https://huggingface.co/badokorach/mobilebert-uncased-squad-v2-finetuned + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mountain_ner_model_en.md b/docs/_posts/ahmedlone127/2024-11-11-mountain_ner_model_en.md new file mode 100644 index 00000000000000..29d92875ae4cb6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mountain_ner_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mountain_ner_model BertForTokenClassification from Shah1st +author: John Snow Labs +name: mountain_ner_model +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mountain_ner_model` is a English model originally trained by Shah1st. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mountain_ner_model_en_5.5.1_3.0_1731298624923.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mountain_ner_model_en_5.5.1_3.0_1731298624923.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') + +tokenClassifier = BertForTokenClassification.pretrained("mountain_ner_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("mountain_ner_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mountain_ner_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Shah1st/mountain-ner-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mountain_ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-mountain_ner_model_pipeline_en.md new file mode 100644 index 00000000000000..41894220bbe460 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mountain_ner_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mountain_ner_model_pipeline pipeline BertForTokenClassification from Shah1st +author: John Snow Labs +name: mountain_ner_model_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mountain_ner_model_pipeline` is a English model originally trained by Shah1st. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mountain_ner_model_pipeline_en_5.5.1_3.0_1731298688183.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mountain_ner_model_pipeline_en_5.5.1_3.0_1731298688183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mountain_ner_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mountain_ner_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mountain_ner_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Shah1st/mountain-ner-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mountain_recognition_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-mountain_recognition_ner_en.md new file mode 100644 index 00000000000000..acfcc435fb47a4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mountain_recognition_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English mountain_recognition_ner BertForTokenClassification from dieumerci +author: John Snow Labs +name: mountain_recognition_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mountain_recognition_ner` is a English model originally trained by dieumerci. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mountain_recognition_ner_en_5.5.1_3.0_1731290821656.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mountain_recognition_ner_en_5.5.1_3.0_1731290821656.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') + +tokenClassifier = BertForTokenClassification.pretrained("mountain_recognition_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("mountain_recognition_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mountain_recognition_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/dieumerci/mountain-recognition-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mountain_recognition_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-mountain_recognition_ner_pipeline_en.md new file mode 100644 index 00000000000000..3ead37a9c09f49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mountain_recognition_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English mountain_recognition_ner_pipeline pipeline BertForTokenClassification from dieumerci +author: John Snow Labs +name: mountain_recognition_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mountain_recognition_ner_pipeline` is a English model originally trained by dieumerci. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mountain_recognition_ner_pipeline_en_5.5.1_3.0_1731290884462.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mountain_recognition_ner_pipeline_en_5.5.1_3.0_1731290884462.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mountain_recognition_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mountain_recognition_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mountain_recognition_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/dieumerci/mountain-recognition-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mpnet_base_all_pittsburgh_squad_en.md b/docs/_posts/ahmedlone127/2024-11-11-mpnet_base_all_pittsburgh_squad_en.md new file mode 100644 index 00000000000000..4e012e211c5f49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mpnet_base_all_pittsburgh_squad_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English mpnet_base_all_pittsburgh_squad MPNetEmbeddings from lizchu414 +author: John Snow Labs +name: mpnet_base_all_pittsburgh_squad +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_all_pittsburgh_squad` is a English model originally trained by lizchu414. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_all_pittsburgh_squad_en_5.5.1_3.0_1731295097151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_all_pittsburgh_squad_en_5.5.1_3.0_1731295097151.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") + +embeddings = MPNetEmbeddings.pretrained("mpnet_base_all_pittsburgh_squad","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("mpnet_base_all_pittsburgh_squad","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_all_pittsburgh_squad| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/lizchu414/mpnet-base-all-pittsburgh-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-mpnet_base_all_pittsburgh_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-mpnet_base_all_pittsburgh_squad_pipeline_en.md new file mode 100644 index 00000000000000..98d7deca55b9c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-mpnet_base_all_pittsburgh_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English mpnet_base_all_pittsburgh_squad_pipeline pipeline MPNetEmbeddings from lizchu414 +author: John Snow Labs +name: mpnet_base_all_pittsburgh_squad_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpnet_base_all_pittsburgh_squad_pipeline` is a English model originally trained by lizchu414. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpnet_base_all_pittsburgh_squad_pipeline_en_5.5.1_3.0_1731295123391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpnet_base_all_pittsburgh_squad_pipeline_en_5.5.1_3.0_1731295123391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("mpnet_base_all_pittsburgh_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("mpnet_base_all_pittsburgh_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpnet_base_all_pittsburgh_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +https://huggingface.co/lizchu414/mpnet-base-all-pittsburgh-squad + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-msu_wiki_ner_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-11-11-msu_wiki_ner_pipeline_ru.md new file mode 100644 index 00000000000000..052a34fd1292cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-msu_wiki_ner_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian msu_wiki_ner_pipeline pipeline BertForTokenClassification from nesemenpolkov +author: John Snow Labs +name: msu_wiki_ner_pipeline +date: 2024-11-11 +tags: [ru, open_source, pipeline, onnx] +task: Named Entity Recognition +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`msu_wiki_ner_pipeline` is a Russian model originally trained by nesemenpolkov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/msu_wiki_ner_pipeline_ru_5.5.1_3.0_1731298735156.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/msu_wiki_ner_pipeline_ru_5.5.1_3.0_1731298735156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("msu_wiki_ner_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("msu_wiki_ner_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|msu_wiki_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|665.1 MB| + +## References + +https://huggingface.co/nesemenpolkov/msu-wiki-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-msu_wiki_ner_ru.md b/docs/_posts/ahmedlone127/2024-11-11-msu_wiki_ner_ru.md new file mode 100644 index 00000000000000..f9978264c43363 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-msu_wiki_ner_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian msu_wiki_ner BertForTokenClassification from nesemenpolkov +author: John Snow Labs +name: msu_wiki_ner +date: 2024-11-11 +tags: [ru, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`msu_wiki_ner` is a Russian model originally trained by nesemenpolkov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/msu_wiki_ner_ru_5.5.1_3.0_1731298695259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/msu_wiki_ner_ru_5.5.1_3.0_1731298695259.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') + +tokenClassifier = BertForTokenClassification.pretrained("msu_wiki_ner","ru") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("msu_wiki_ner", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|msu_wiki_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ru| +|Size:|665.1 MB| + +## References + +https://huggingface.co/nesemenpolkov/msu-wiki-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nasa_smd_ibm_v0_1_uat_labeler_en.md b/docs/_posts/ahmedlone127/2024-11-11-nasa_smd_ibm_v0_1_uat_labeler_en.md new file mode 100644 index 00000000000000..bb7386e46fce77 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nasa_smd_ibm_v0_1_uat_labeler_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nasa_smd_ibm_v0_1_uat_labeler RoBertaForTokenClassification from adsabs +author: John Snow Labs +name: nasa_smd_ibm_v0_1_uat_labeler +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nasa_smd_ibm_v0_1_uat_labeler` is a English model originally trained by adsabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_v0_1_uat_labeler_en_5.5.1_3.0_1731310993704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_v0_1_uat_labeler_en_5.5.1_3.0_1731310993704.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("nasa_smd_ibm_v0_1_uat_labeler","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("nasa_smd_ibm_v0_1_uat_labeler", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nasa_smd_ibm_v0_1_uat_labeler| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|472.8 MB| + +## References + +https://huggingface.co/adsabs/nasa-smd-ibm-v0.1_UAT_Labeler \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nasa_smd_ibm_v0_1_uat_labeler_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-nasa_smd_ibm_v0_1_uat_labeler_pipeline_en.md new file mode 100644 index 00000000000000..1d21f37f04d8ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nasa_smd_ibm_v0_1_uat_labeler_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nasa_smd_ibm_v0_1_uat_labeler_pipeline pipeline RoBertaForTokenClassification from adsabs +author: John Snow Labs +name: nasa_smd_ibm_v0_1_uat_labeler_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nasa_smd_ibm_v0_1_uat_labeler_pipeline` is a English model originally trained by adsabs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_v0_1_uat_labeler_pipeline_en_5.5.1_3.0_1731311018084.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nasa_smd_ibm_v0_1_uat_labeler_pipeline_en_5.5.1_3.0_1731311018084.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nasa_smd_ibm_v0_1_uat_labeler_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nasa_smd_ibm_v0_1_uat_labeler_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nasa_smd_ibm_v0_1_uat_labeler_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|472.8 MB| + +## References + +https://huggingface.co/adsabs/nasa-smd-ibm-v0.1_UAT_Labeler + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nees_bert_base_portuguese_cased_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-nees_bert_base_portuguese_cased_finetuned_ner_en.md new file mode 100644 index 00000000000000..23812f06211044 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nees_bert_base_portuguese_cased_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nees_bert_base_portuguese_cased_finetuned_ner BertForTokenClassification from yuridrcosta +author: John Snow Labs +name: nees_bert_base_portuguese_cased_finetuned_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nees_bert_base_portuguese_cased_finetuned_ner` is a English model originally trained by yuridrcosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nees_bert_base_portuguese_cased_finetuned_ner_en_5.5.1_3.0_1731290402339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nees_bert_base_portuguese_cased_finetuned_ner_en_5.5.1_3.0_1731290402339.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') + +tokenClassifier = BertForTokenClassification.pretrained("nees_bert_base_portuguese_cased_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("nees_bert_base_portuguese_cased_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nees_bert_base_portuguese_cased_finetuned_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/yuridrcosta/nees-bert-base-portuguese-cased-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nees_bert_base_portuguese_cased_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-nees_bert_base_portuguese_cased_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..62bd04fcc78147 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nees_bert_base_portuguese_cased_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nees_bert_base_portuguese_cased_finetuned_ner_pipeline pipeline BertForTokenClassification from yuridrcosta +author: John Snow Labs +name: nees_bert_base_portuguese_cased_finetuned_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nees_bert_base_portuguese_cased_finetuned_ner_pipeline` is a English model originally trained by yuridrcosta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nees_bert_base_portuguese_cased_finetuned_ner_pipeline_en_5.5.1_3.0_1731290424071.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nees_bert_base_portuguese_cased_finetuned_ner_pipeline_en_5.5.1_3.0_1731290424071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nees_bert_base_portuguese_cased_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nees_bert_base_portuguese_cased_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nees_bert_base_portuguese_cased_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/yuridrcosta/nees-bert-base-portuguese-cased-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nepal_bhasa_biored_model_en.md b/docs/_posts/ahmedlone127/2024-11-11-nepal_bhasa_biored_model_en.md new file mode 100644 index 00000000000000..7b17b75e6b2a00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nepal_bhasa_biored_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nepal_bhasa_biored_model BertForTokenClassification from c-x-he +author: John Snow Labs +name: nepal_bhasa_biored_model +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_biored_model` is a English model originally trained by c-x-he. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_biored_model_en_5.5.1_3.0_1731299083922.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_biored_model_en_5.5.1_3.0_1731299083922.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') + +tokenClassifier = BertForTokenClassification.pretrained("nepal_bhasa_biored_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("nepal_bhasa_biored_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nepal_bhasa_biored_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/c-x-he/New_BioRED_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nepal_bhasa_biored_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-nepal_bhasa_biored_model_pipeline_en.md new file mode 100644 index 00000000000000..1e9e12dce5f0ff --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nepal_bhasa_biored_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nepal_bhasa_biored_model_pipeline pipeline BertForTokenClassification from c-x-he +author: John Snow Labs +name: nepal_bhasa_biored_model_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nepal_bhasa_biored_model_pipeline` is a English model originally trained by c-x-he. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nepal_bhasa_biored_model_pipeline_en_5.5.1_3.0_1731299109074.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nepal_bhasa_biored_model_pipeline_en_5.5.1_3.0_1731299109074.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nepal_bhasa_biored_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nepal_bhasa_biored_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nepal_bhasa_biored_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/c-x-he/New_BioRED_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_en.md b/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_en.md new file mode 100644 index 00000000000000..ca901d075e86d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ner_finetuning_beto BertForTokenClassification from raulgdp +author: John Snow Labs +name: ner_finetuning_beto +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_finetuning_beto` is a English model originally trained by raulgdp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_finetuning_beto_en_5.5.1_3.0_1731290423097.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_finetuning_beto_en_5.5.1_3.0_1731290423097.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') + +tokenClassifier = BertForTokenClassification.pretrained("ner_finetuning_beto","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("ner_finetuning_beto", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_finetuning_beto| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/raulgdp/NER-finetuning-BETO \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pipeline_en.md new file mode 100644 index 00000000000000..aca24b66ba6ff9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_finetuning_beto_pipeline pipeline BertForTokenClassification from raulgdp +author: John Snow Labs +name: ner_finetuning_beto_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_finetuning_beto_pipeline` is a English model originally trained by raulgdp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_finetuning_beto_pipeline_en_5.5.1_3.0_1731290448484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_finetuning_beto_pipeline_en_5.5.1_3.0_1731290448484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_finetuning_beto_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_finetuning_beto_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_finetuning_beto_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/raulgdp/NER-finetuning-BETO + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pro_en.md b/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pro_en.md new file mode 100644 index 00000000000000..f227572b453a38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pro_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ner_finetuning_beto_pro BertForTokenClassification from raulgdp +author: John Snow Labs +name: ner_finetuning_beto_pro +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_finetuning_beto_pro` is a English model originally trained by raulgdp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_finetuning_beto_pro_en_5.5.1_3.0_1731290926725.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_finetuning_beto_pro_en_5.5.1_3.0_1731290926725.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') + +tokenClassifier = BertForTokenClassification.pretrained("ner_finetuning_beto_pro","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("ner_finetuning_beto_pro", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_finetuning_beto_pro| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/raulgdp/NER-finetuning-BETO-PRO \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pro_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pro_pipeline_en.md new file mode 100644 index 00000000000000..86b6c7d149b34b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_finetuning_beto_pro_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_finetuning_beto_pro_pipeline pipeline BertForTokenClassification from raulgdp +author: John Snow Labs +name: ner_finetuning_beto_pro_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_finetuning_beto_pro_pipeline` is a English model originally trained by raulgdp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_finetuning_beto_pro_pipeline_en_5.5.1_3.0_1731290947906.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_finetuning_beto_pro_pipeline_en_5.5.1_3.0_1731290947906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_finetuning_beto_pro_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_finetuning_beto_pro_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_finetuning_beto_pro_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/raulgdp/NER-finetuning-BETO-PRO + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_model_en.md b/docs/_posts/ahmedlone127/2024-11-11-ner_model_en.md new file mode 100644 index 00000000000000..184b8ed0fb9ff0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ner_model BertForTokenClassification from MichaelSargious +author: John Snow Labs +name: ner_model +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model` is a English model originally trained by MichaelSargious. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_en_5.5.1_3.0_1731290717439.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_en_5.5.1_3.0_1731290717439.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') + +tokenClassifier = BertForTokenClassification.pretrained("ner_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("ner_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/MichaelSargious/ner_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-ner_model_pipeline_en.md new file mode 100644 index 00000000000000..a38e0bd1042ce6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_model_pipeline pipeline BertForTokenClassification from MichaelSargious +author: John Snow Labs +name: ner_model_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_model_pipeline` is a English model originally trained by MichaelSargious. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_model_pipeline_en_5.5.1_3.0_1731290752686.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_model_pipeline_en_5.5.1_3.0_1731290752686.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/MichaelSargious/ner_model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_tokenclassification_persian_en.md b/docs/_posts/ahmedlone127/2024-11-11-ner_tokenclassification_persian_en.md new file mode 100644 index 00000000000000..de9e6d9f0963be --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_tokenclassification_persian_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ner_tokenclassification_persian BertForTokenClassification from AidAFadaeian +author: John Snow Labs +name: ner_tokenclassification_persian +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_tokenclassification_persian` is a English model originally trained by AidAFadaeian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_tokenclassification_persian_en_5.5.1_3.0_1731298967003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_tokenclassification_persian_en_5.5.1_3.0_1731298967003.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') + +tokenClassifier = BertForTokenClassification.pretrained("ner_tokenclassification_persian","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("ner_tokenclassification_persian", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_tokenclassification_persian| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|606.6 MB| + +## References + +https://huggingface.co/AidAFadaeian/NER_tokenclassification_persian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_tokenclassification_persian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-ner_tokenclassification_persian_pipeline_en.md new file mode 100644 index 00000000000000..6eaca66cadd93a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_tokenclassification_persian_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ner_tokenclassification_persian_pipeline pipeline BertForTokenClassification from AidAFadaeian +author: John Snow Labs +name: ner_tokenclassification_persian_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_tokenclassification_persian_pipeline` is a English model originally trained by AidAFadaeian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_tokenclassification_persian_pipeline_en_5.5.1_3.0_1731298999068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_tokenclassification_persian_pipeline_en_5.5.1_3.0_1731298999068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_tokenclassification_persian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_tokenclassification_persian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_tokenclassification_persian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|606.6 MB| + +## References + +https://huggingface.co/AidAFadaeian/NER_tokenclassification_persian + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_xlmr_pipeline_xx.md b/docs/_posts/ahmedlone127/2024-11-11-ner_xlmr_pipeline_xx.md new file mode 100644 index 00000000000000..b8f08c1fba4434 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_xlmr_pipeline_xx.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Multilingual ner_xlmr_pipeline pipeline XlmRoBertaForTokenClassification from programmersilvanus +author: John Snow Labs +name: ner_xlmr_pipeline +date: 2024-11-11 +tags: [xx, open_source, pipeline, onnx] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_xlmr_pipeline` is a Multilingual model originally trained by programmersilvanus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_xlmr_pipeline_xx_5.5.1_3.0_1731293483443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_xlmr_pipeline_xx_5.5.1_3.0_1731293483443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ner_xlmr_pipeline", lang = "xx") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ner_xlmr_pipeline", lang = "xx") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_xlmr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|832.6 MB| + +## References + +https://huggingface.co/programmersilvanus/ner-xlmr + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ner_xlmr_xx.md b/docs/_posts/ahmedlone127/2024-11-11-ner_xlmr_xx.md new file mode 100644 index 00000000000000..2f8c9718aa9e4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ner_xlmr_xx.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Multilingual ner_xlmr XlmRoBertaForTokenClassification from programmersilvanus +author: John Snow Labs +name: ner_xlmr +date: 2024-11-11 +tags: [xx, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: xx +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ner_xlmr` is a Multilingual model originally trained by programmersilvanus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ner_xlmr_xx_5.5.1_3.0_1731293392020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ner_xlmr_xx_5.5.1_3.0_1731293392020.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') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner_xlmr","xx") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("ner_xlmr", "xx") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ner_xlmr| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|xx| +|Size:|832.6 MB| + +## References + +https://huggingface.co/programmersilvanus/ner-xlmr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nerugm_base_3_id.md b/docs/_posts/ahmedlone127/2024-11-11-nerugm_base_3_id.md new file mode 100644 index 00000000000000..24b935db19a2b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nerugm_base_3_id.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Indonesian nerugm_base_3 BertForTokenClassification from apwic +author: John Snow Labs +name: nerugm_base_3 +date: 2024-11-11 +tags: [id, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: id +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nerugm_base_3` is a Indonesian model originally trained by apwic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nerugm_base_3_id_5.5.1_3.0_1731285227978.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nerugm_base_3_id_5.5.1_3.0_1731285227978.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') + +tokenClassifier = BertForTokenClassification.pretrained("nerugm_base_3","id") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("nerugm_base_3", "id") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nerugm_base_3| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|id| +|Size:|411.8 MB| + +## References + +https://huggingface.co/apwic/nerugm-base-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nerugm_base_3_pipeline_id.md b/docs/_posts/ahmedlone127/2024-11-11-nerugm_base_3_pipeline_id.md new file mode 100644 index 00000000000000..be21a734240864 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nerugm_base_3_pipeline_id.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Indonesian nerugm_base_3_pipeline pipeline BertForTokenClassification from apwic +author: John Snow Labs +name: nerugm_base_3_pipeline +date: 2024-11-11 +tags: [id, open_source, pipeline, onnx] +task: Named Entity Recognition +language: id +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nerugm_base_3_pipeline` is a Indonesian model originally trained by apwic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nerugm_base_3_pipeline_id_5.5.1_3.0_1731285257868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nerugm_base_3_pipeline_id_5.5.1_3.0_1731285257868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nerugm_base_3_pipeline", lang = "id") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nerugm_base_3_pipeline", lang = "id") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nerugm_base_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|id| +|Size:|411.8 MB| + +## References + +https://huggingface.co/apwic/nerugm-base-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nlp_tutorial_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-nlp_tutorial_ner_en.md new file mode 100644 index 00000000000000..273a281d2141fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nlp_tutorial_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nlp_tutorial_ner BertForTokenClassification from Conan-Lao +author: John Snow Labs +name: nlp_tutorial_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tutorial_ner` is a English model originally trained by Conan-Lao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tutorial_ner_en_5.5.1_3.0_1731290341170.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tutorial_ner_en_5.5.1_3.0_1731290341170.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') + +tokenClassifier = BertForTokenClassification.pretrained("nlp_tutorial_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("nlp_tutorial_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_tutorial_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/Conan-Lao/nlp_tutorial_ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nlp_tutorial_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-nlp_tutorial_ner_pipeline_en.md new file mode 100644 index 00000000000000..f5fdf808a7e70c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nlp_tutorial_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nlp_tutorial_ner_pipeline pipeline BertForTokenClassification from Conan-Lao +author: John Snow Labs +name: nlp_tutorial_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nlp_tutorial_ner_pipeline` is a English model originally trained by Conan-Lao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nlp_tutorial_ner_pipeline_en_5.5.1_3.0_1731290362432.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nlp_tutorial_ner_pipeline_en_5.5.1_3.0_1731290362432.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nlp_tutorial_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nlp_tutorial_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nlp_tutorial_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/Conan-Lao/nlp_tutorial_ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_en.md b/docs/_posts/ahmedlone127/2024-11-11-norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_en.md new file mode 100644 index 00000000000000..3a0a51b8d3fd9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp BertForQuestionAnswering from eanderson +author: John Snow Labs +name: norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp` is a English model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_en_5.5.1_3.0_1731289481925.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_en_5.5.1_3.0_1731289481925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|666.2 MB| + +## References + +https://huggingface.co/eanderson/nb-bert-base-qa-squad-nb_v2_temp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en.md new file mode 100644 index 00000000000000..5c6816c1f92b65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline pipeline BertForQuestionAnswering from eanderson +author: John Snow Labs +name: norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline` is a English model originally trained by eanderson. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en_5.5.1_3.0_1731289516281.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline_en_5.5.1_3.0_1731289516281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norwegian_bokml_bert_base_qa_squad_norwegian_bokml_v2_temp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|666.2 MB| + +## References + +https://huggingface.co/eanderson/nb-bert-base-qa-squad-nb_v2_temp + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nusabert_base_posp_en.md b/docs/_posts/ahmedlone127/2024-11-11-nusabert_base_posp_en.md new file mode 100644 index 00000000000000..ffab257ec4f50b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nusabert_base_posp_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English nusabert_base_posp BertForTokenClassification from LazarusNLP +author: John Snow Labs +name: nusabert_base_posp +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nusabert_base_posp` is a English model originally trained by LazarusNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nusabert_base_posp_en_5.5.1_3.0_1731285880660.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nusabert_base_posp_en_5.5.1_3.0_1731285880660.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') + +tokenClassifier = BertForTokenClassification.pretrained("nusabert_base_posp","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("nusabert_base_posp", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nusabert_base_posp| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|412.5 MB| + +## References + +https://huggingface.co/LazarusNLP/NusaBERT-base-POSP \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-nusabert_base_posp_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-nusabert_base_posp_pipeline_en.md new file mode 100644 index 00000000000000..138b88f6fe0d26 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-nusabert_base_posp_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English nusabert_base_posp_pipeline pipeline BertForTokenClassification from LazarusNLP +author: John Snow Labs +name: nusabert_base_posp_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nusabert_base_posp_pipeline` is a English model originally trained by LazarusNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nusabert_base_posp_pipeline_en_5.5.1_3.0_1731285902489.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nusabert_base_posp_pipeline_en_5.5.1_3.0_1731285902489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("nusabert_base_posp_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("nusabert_base_posp_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nusabert_base_posp_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.5 MB| + +## References + +https://huggingface.co/LazarusNLP/NusaBERT-base-POSP + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-persian_text_ner_bert_v1_fa.md b/docs/_posts/ahmedlone127/2024-11-11-persian_text_ner_bert_v1_fa.md new file mode 100644 index 00000000000000..32d1574f8c3718 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-persian_text_ner_bert_v1_fa.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Persian persian_text_ner_bert_v1 BertForTokenClassification from SeyedAli +author: John Snow Labs +name: persian_text_ner_bert_v1 +date: 2024-11-11 +tags: [fa, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: fa +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`persian_text_ner_bert_v1` is a Persian model originally trained by SeyedAli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/persian_text_ner_bert_v1_fa_5.5.1_3.0_1731299048875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/persian_text_ner_bert_v1_fa_5.5.1_3.0_1731299048875.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') + +tokenClassifier = BertForTokenClassification.pretrained("persian_text_ner_bert_v1","fa") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("persian_text_ner_bert_v1", "fa") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|persian_text_ner_bert_v1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|fa| +|Size:|606.6 MB| + +## References + +https://huggingface.co/SeyedAli/Persian-Text-NER-Bert-V1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-persian_text_ner_bert_v1_pipeline_fa.md b/docs/_posts/ahmedlone127/2024-11-11-persian_text_ner_bert_v1_pipeline_fa.md new file mode 100644 index 00000000000000..06ba601147d270 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-persian_text_ner_bert_v1_pipeline_fa.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Persian persian_text_ner_bert_v1_pipeline pipeline BertForTokenClassification from SeyedAli +author: John Snow Labs +name: persian_text_ner_bert_v1_pipeline +date: 2024-11-11 +tags: [fa, open_source, pipeline, onnx] +task: Named Entity Recognition +language: fa +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`persian_text_ner_bert_v1_pipeline` is a Persian model originally trained by SeyedAli. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/persian_text_ner_bert_v1_pipeline_fa_5.5.1_3.0_1731299082120.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/persian_text_ner_bert_v1_pipeline_fa_5.5.1_3.0_1731299082120.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("persian_text_ner_bert_v1_pipeline", lang = "fa") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("persian_text_ner_bert_v1_pipeline", lang = "fa") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|persian_text_ner_bert_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|fa| +|Size:|606.6 MB| + +## References + +https://huggingface.co/SeyedAli/Persian-Text-NER-Bert-V1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-personalinfoclassifier_en.md b/docs/_posts/ahmedlone127/2024-11-11-personalinfoclassifier_en.md new file mode 100644 index 00000000000000..e739f4b8c1dc41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-personalinfoclassifier_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English personalinfoclassifier BertForSequenceClassification from MrAB01 +author: John Snow Labs +name: personalinfoclassifier +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`personalinfoclassifier` is a English model originally trained by MrAB01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/personalinfoclassifier_en_5.5.1_3.0_1731309188691.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/personalinfoclassifier_en_5.5.1_3.0_1731309188691.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("personalinfoclassifier","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("personalinfoclassifier", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|personalinfoclassifier| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/MrAB01/PersonalInfoClassifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-personalinfoclassifier_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-personalinfoclassifier_pipeline_en.md new file mode 100644 index 00000000000000..099794319e615b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-personalinfoclassifier_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English personalinfoclassifier_pipeline pipeline BertForSequenceClassification from MrAB01 +author: John Snow Labs +name: personalinfoclassifier_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`personalinfoclassifier_pipeline` is a English model originally trained by MrAB01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/personalinfoclassifier_pipeline_en_5.5.1_3.0_1731309210318.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/personalinfoclassifier_pipeline_en_5.5.1_3.0_1731309210318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("personalinfoclassifier_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("personalinfoclassifier_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|personalinfoclassifier_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/MrAB01/PersonalInfoClassifier + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-politeness_model_en.md b/docs/_posts/ahmedlone127/2024-11-11-politeness_model_en.md new file mode 100644 index 00000000000000..54b7e18676d712 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-politeness_model_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English politeness_model BertForSequenceClassification from gljj +author: John Snow Labs +name: politeness_model +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`politeness_model` is a English model originally trained by gljj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/politeness_model_en_5.5.1_3.0_1731310062293.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/politeness_model_en_5.5.1_3.0_1731310062293.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("politeness_model","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("politeness_model", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|politeness_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gljj/politeness-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-politeness_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-politeness_model_pipeline_en.md new file mode 100644 index 00000000000000..ae45b23ba3f142 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-politeness_model_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English politeness_model_pipeline pipeline BertForSequenceClassification from gljj +author: John Snow Labs +name: politeness_model_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`politeness_model_pipeline` is a English model originally trained by gljj. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/politeness_model_pipeline_en_5.5.1_3.0_1731310084610.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/politeness_model_pipeline_en_5.5.1_3.0_1731310084610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("politeness_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("politeness_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|politeness_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gljj/politeness-model + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-popbert_de.md b/docs/_posts/ahmedlone127/2024-11-11-popbert_de.md new file mode 100644 index 00000000000000..67f9fa00c1f2f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-popbert_de.md @@ -0,0 +1,94 @@ +--- +layout: model +title: German popbert BertForSequenceClassification from luerhard +author: John Snow Labs +name: popbert +date: 2024-11-11 +tags: [de, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: de +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`popbert` is a German model originally trained by luerhard. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/popbert_de_5.5.1_3.0_1731309940376.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/popbert_de_5.5.1_3.0_1731309940376.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("popbert","de") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("popbert", "de") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|popbert| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|1.3 GB| + +## References + +https://huggingface.co/luerhard/PopBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-popbert_pipeline_de.md b/docs/_posts/ahmedlone127/2024-11-11-popbert_pipeline_de.md new file mode 100644 index 00000000000000..7e5575a55024d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-popbert_pipeline_de.md @@ -0,0 +1,72 @@ +--- +layout: model +title: German popbert_pipeline pipeline BertForSequenceClassification from luerhard +author: John Snow Labs +name: popbert_pipeline +date: 2024-11-11 +tags: [de, open_source, pipeline, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`popbert_pipeline` is a German model originally trained by luerhard. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/popbert_pipeline_de_5.5.1_3.0_1731310008414.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/popbert_pipeline_de_5.5.1_3.0_1731310008414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("popbert_pipeline", lang = "de") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("popbert_pipeline", lang = "de") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|popbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|de| +|Size:|1.3 GB| + +## References + +References + +https://huggingface.co/luerhard/PopBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-pretrain_finetuned_v2_en.md b/docs/_posts/ahmedlone127/2024-11-11-pretrain_finetuned_v2_en.md new file mode 100644 index 00000000000000..3db9d5e6492766 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-pretrain_finetuned_v2_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English pretrain_finetuned_v2 BertForQuestionAnswering from marinaibr +author: John Snow Labs +name: pretrain_finetuned_v2 +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`pretrain_finetuned_v2` is a English model originally trained by marinaibr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrain_finetuned_v2_en_5.5.1_3.0_1731289827138.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrain_finetuned_v2_en_5.5.1_3.0_1731289827138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("pretrain_finetuned_v2","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("pretrain_finetuned_v2", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pretrain_finetuned_v2| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.8 MB| + +## References + +https://huggingface.co/marinaibr/pretrain-finetuned-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-pretrain_finetuned_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-pretrain_finetuned_v2_pipeline_en.md new file mode 100644 index 00000000000000..ea7a8596f7dd96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-pretrain_finetuned_v2_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English pretrain_finetuned_v2_pipeline pipeline BertForQuestionAnswering from marinaibr +author: John Snow Labs +name: pretrain_finetuned_v2_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pretrain_finetuned_v2_pipeline` is a English model originally trained by marinaibr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pretrain_finetuned_v2_pipeline_en_5.5.1_3.0_1731289848049.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pretrain_finetuned_v2_pipeline_en_5.5.1_3.0_1731289848049.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pretrain_finetuned_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pretrain_finetuned_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pretrain_finetuned_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.9 MB| + +## References + +https://huggingface.co/marinaibr/pretrain-finetuned-v2 + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-procedure_tool_matching_10_epochs_en.md b/docs/_posts/ahmedlone127/2024-11-11-procedure_tool_matching_10_epochs_en.md new file mode 100644 index 00000000000000..ae7a586b6d8401 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-procedure_tool_matching_10_epochs_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English procedure_tool_matching_10_epochs MPNetEmbeddings from brilan +author: John Snow Labs +name: procedure_tool_matching_10_epochs +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`procedure_tool_matching_10_epochs` is a English model originally trained by brilan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/procedure_tool_matching_10_epochs_en_5.5.1_3.0_1731294702325.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/procedure_tool_matching_10_epochs_en_5.5.1_3.0_1731294702325.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") + +embeddings = MPNetEmbeddings.pretrained("procedure_tool_matching_10_epochs","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("procedure_tool_matching_10_epochs","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|procedure_tool_matching_10_epochs| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/brilan/procedure-tool-matching_10_epochs \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-procedure_tool_matching_10_epochs_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-procedure_tool_matching_10_epochs_pipeline_en.md new file mode 100644 index 00000000000000..cd0aabc0210a34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-procedure_tool_matching_10_epochs_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English procedure_tool_matching_10_epochs_pipeline pipeline MPNetEmbeddings from brilan +author: John Snow Labs +name: procedure_tool_matching_10_epochs_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`procedure_tool_matching_10_epochs_pipeline` is a English model originally trained by brilan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/procedure_tool_matching_10_epochs_pipeline_en_5.5.1_3.0_1731294728804.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/procedure_tool_matching_10_epochs_pipeline_en_5.5.1_3.0_1731294728804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("procedure_tool_matching_10_epochs_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("procedure_tool_matching_10_epochs_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|procedure_tool_matching_10_epochs_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/brilan/procedure-tool-matching_10_epochs + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-product_model_en.md b/docs/_posts/ahmedlone127/2024-11-11-product_model_en.md new file mode 100644 index 00000000000000..01ff8c7b0b9f05 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-product_model_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English product_model MPNetEmbeddings from alpcansoydas +author: John Snow Labs +name: product_model +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_model` is a English model originally trained by alpcansoydas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_model_en_5.5.1_3.0_1731295066547.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_model_en_5.5.1_3.0_1731295066547.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") + +embeddings = MPNetEmbeddings.pretrained("product_model","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("product_model","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|product_model| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/alpcansoydas/product-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-product_model_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-product_model_pipeline_en.md new file mode 100644 index 00000000000000..5509af1db40ee6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-product_model_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English product_model_pipeline pipeline MPNetEmbeddings from alpcansoydas +author: John Snow Labs +name: product_model_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_model_pipeline` is a English model originally trained by alpcansoydas. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_model_pipeline_en_5.5.1_3.0_1731295088962.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_model_pipeline_en_5.5.1_3.0_1731295088962.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("product_model_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("product_model_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|product_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.7 MB| + +## References + +https://huggingface.co/alpcansoydas/product-model + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-product_recognize_en.md b/docs/_posts/ahmedlone127/2024-11-11-product_recognize_en.md new file mode 100644 index 00000000000000..c911f6eae3a7a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-product_recognize_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English product_recognize BertForTokenClassification from HentDios +author: John Snow Labs +name: product_recognize +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_recognize` is a English model originally trained by HentDios. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_recognize_en_5.5.1_3.0_1731285314999.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_recognize_en_5.5.1_3.0_1731285314999.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') + +tokenClassifier = BertForTokenClassification.pretrained("product_recognize","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("product_recognize", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|product_recognize| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/HentDios/product-recognize \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-product_recognize_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-product_recognize_pipeline_en.md new file mode 100644 index 00000000000000..b3c35a440d49d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-product_recognize_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English product_recognize_pipeline pipeline BertForTokenClassification from HentDios +author: John Snow Labs +name: product_recognize_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`product_recognize_pipeline` is a English model originally trained by HentDios. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/product_recognize_pipeline_en_5.5.1_3.0_1731285338977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/product_recognize_pipeline_en_5.5.1_3.0_1731285338977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("product_recognize_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("product_recognize_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|product_recognize_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/HentDios/product-recognize + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-propaganda_ner_arabic_ar.md b/docs/_posts/ahmedlone127/2024-11-11-propaganda_ner_arabic_ar.md new file mode 100644 index 00000000000000..5c205e9c4b4111 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-propaganda_ner_arabic_ar.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Arabic propaganda_ner_arabic BertForTokenClassification from ashrafulparan +author: John Snow Labs +name: propaganda_ner_arabic +date: 2024-11-11 +tags: [ar, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`propaganda_ner_arabic` is a Arabic model originally trained by ashrafulparan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/propaganda_ner_arabic_ar_5.5.1_3.0_1731290522918.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/propaganda_ner_arabic_ar_5.5.1_3.0_1731290522918.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') + +tokenClassifier = BertForTokenClassification.pretrained("propaganda_ner_arabic","ar") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("propaganda_ner_arabic", "ar") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|propaganda_ner_arabic| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|406.7 MB| + +## References + +https://huggingface.co/ashrafulparan/Propaganda-NER-Arabic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-propaganda_ner_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-11-11-propaganda_ner_arabic_pipeline_ar.md new file mode 100644 index 00000000000000..f4e3da52799e79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-propaganda_ner_arabic_pipeline_ar.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Arabic propaganda_ner_arabic_pipeline pipeline BertForTokenClassification from ashrafulparan +author: John Snow Labs +name: propaganda_ner_arabic_pipeline +date: 2024-11-11 +tags: [ar, open_source, pipeline, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`propaganda_ner_arabic_pipeline` is a Arabic model originally trained by ashrafulparan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/propaganda_ner_arabic_pipeline_ar_5.5.1_3.0_1731290544801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/propaganda_ner_arabic_pipeline_ar_5.5.1_3.0_1731290544801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("propaganda_ner_arabic_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("propaganda_ner_arabic_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|propaganda_ner_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|406.8 MB| + +## References + +https://huggingface.co/ashrafulparan/Propaganda-NER-Arabic + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-pubmedbert_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-pubmedbert_finetuned_ner_en.md new file mode 100644 index 00000000000000..7f8355299d1d55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-pubmedbert_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English pubmedbert_finetuned_ner BertForTokenClassification from jialinselenasong +author: John Snow Labs +name: pubmedbert_finetuned_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubmedbert_finetuned_ner` is a English model originally trained by jialinselenasong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubmedbert_finetuned_ner_en_5.5.1_3.0_1731290761905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubmedbert_finetuned_ner_en_5.5.1_3.0_1731290761905.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') + +tokenClassifier = BertForTokenClassification.pretrained("pubmedbert_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("pubmedbert_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pubmedbert_finetuned_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/jialinselenasong/pubmedbert-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-pubmedbert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-pubmedbert_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..9b2030be9980a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-pubmedbert_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English pubmedbert_finetuned_ner_pipeline pipeline BertForTokenClassification from jialinselenasong +author: John Snow Labs +name: pubmedbert_finetuned_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pubmedbert_finetuned_ner_pipeline` is a English model originally trained by jialinselenasong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pubmedbert_finetuned_ner_pipeline_en_5.5.1_3.0_1731290786027.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pubmedbert_finetuned_ner_pipeline_en_5.5.1_3.0_1731290786027.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("pubmedbert_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("pubmedbert_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pubmedbert_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.2 MB| + +## References + +https://huggingface.co/jialinselenasong/pubmedbert-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-qa_model_balchid_en.md b/docs/_posts/ahmedlone127/2024-11-11-qa_model_balchid_en.md new file mode 100644 index 00000000000000..33ca00f12234a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-qa_model_balchid_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English qa_model_balchid BertForQuestionAnswering from balchid +author: John Snow Labs +name: qa_model_balchid +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`qa_model_balchid` is a English model originally trained by balchid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_balchid_en_5.5.1_3.0_1731289028794.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_balchid_en_5.5.1_3.0_1731289028794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("qa_model_balchid","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("qa_model_balchid", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_model_balchid| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/balchid/qa_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-qa_model_balchid_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-qa_model_balchid_pipeline_en.md new file mode 100644 index 00000000000000..5159bb9652d99d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-qa_model_balchid_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English qa_model_balchid_pipeline pipeline BertForQuestionAnswering from balchid +author: John Snow Labs +name: qa_model_balchid_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qa_model_balchid_pipeline` is a English model originally trained by balchid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qa_model_balchid_pipeline_en_5.5.1_3.0_1731289051251.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qa_model_balchid_pipeline_en_5.5.1_3.0_1731289051251.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("qa_model_balchid_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("qa_model_balchid_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qa_model_balchid_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.2 MB| + +## References + +https://huggingface.co/balchid/qa_model + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-quote_model_bertm_v1_en.md b/docs/_posts/ahmedlone127/2024-11-11-quote_model_bertm_v1_en.md new file mode 100644 index 00000000000000..a7d99077559c50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-quote_model_bertm_v1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English quote_model_bertm_v1 BertForTokenClassification from Iceland +author: John Snow Labs +name: quote_model_bertm_v1 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`quote_model_bertm_v1` is a English model originally trained by Iceland. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/quote_model_bertm_v1_en_5.5.1_3.0_1731298749377.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/quote_model_bertm_v1_en_5.5.1_3.0_1731298749377.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') + +tokenClassifier = BertForTokenClassification.pretrained("quote_model_bertm_v1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("quote_model_bertm_v1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|quote_model_bertm_v1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/Iceland/quote-model-BERTm-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-quote_model_bertm_v1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-quote_model_bertm_v1_pipeline_en.md new file mode 100644 index 00000000000000..eeff29fc89a209 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-quote_model_bertm_v1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English quote_model_bertm_v1_pipeline pipeline BertForTokenClassification from Iceland +author: John Snow Labs +name: quote_model_bertm_v1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`quote_model_bertm_v1_pipeline` is a English model originally trained by Iceland. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/quote_model_bertm_v1_pipeline_en_5.5.1_3.0_1731298784216.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/quote_model_bertm_v1_pipeline_en_5.5.1_3.0_1731298784216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("quote_model_bertm_v1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("quote_model_bertm_v1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|quote_model_bertm_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.1 MB| + +## References + +https://huggingface.co/Iceland/quote-model-BERTm-v1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-results_en.md b/docs/_posts/ahmedlone127/2024-11-11-results_en.md new file mode 100644 index 00000000000000..a13d5742fcd173 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-results_en.md @@ -0,0 +1,96 @@ +--- +layout: model +title: English results DistilBertForQuestionAnswering from Souvik123 +author: John Snow Labs +name: results +date: 2024-11-11 +tags: [distilbert, en, open_source, question_answering, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results` is a English model originally trained by Souvik123. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_en_5.5.1_3.0_1731301209851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_en_5.5.1_3.0_1731301209851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +document_assembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + + +spanClassifier = DistilBertForQuestionAnswering.pretrained("results","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([document_assembler, spanClassifier]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) +``` +```scala +val document_assembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = DistilBertForQuestionAnswering + .pretrained("results", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(document_assembler, spanClassifier)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|results| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.2 MB| + +## References + +References + +References + +References + +https://huggingface.co/Souvik123/results \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-results_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-results_pipeline_en.md new file mode 100644 index 00000000000000..6c723b057ba53e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-results_pipeline_en.md @@ -0,0 +1,72 @@ +--- +layout: model +title: English results_pipeline pipeline RoBertaForTokenClassification from danielyoo +author: John Snow Labs +name: results_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_pipeline` is a English model originally trained by danielyoo. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_pipeline_en_5.5.1_3.0_1731301232582.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_pipeline_en_5.5.1_3.0_1731301232582.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("results_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("results_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|results_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.2 MB| + +## References + +References + +https://huggingface.co/danielyoo/results + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_base_absa_ate_sentiment_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_absa_ate_sentiment_en.md new file mode 100644 index 00000000000000..bcfcac9683d809 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_absa_ate_sentiment_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_absa_ate_sentiment RoBertaForTokenClassification from gauneg +author: John Snow Labs +name: roberta_base_absa_ate_sentiment +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_absa_ate_sentiment` is a English model originally trained by gauneg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_absa_ate_sentiment_en_5.5.1_3.0_1731314074640.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_absa_ate_sentiment_en_5.5.1_3.0_1731314074640.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_absa_ate_sentiment","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_absa_ate_sentiment", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_absa_ate_sentiment| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|451.2 MB| + +## References + +https://huggingface.co/gauneg/roberta-base-absa-ate-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_base_absa_ate_sentiment_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_absa_ate_sentiment_pipeline_en.md new file mode 100644 index 00000000000000..80bc7b25f26e26 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_absa_ate_sentiment_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_absa_ate_sentiment_pipeline pipeline RoBertaForTokenClassification from gauneg +author: John Snow Labs +name: roberta_base_absa_ate_sentiment_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_absa_ate_sentiment_pipeline` is a English model originally trained by gauneg. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_absa_ate_sentiment_pipeline_en_5.5.1_3.0_1731314099373.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_absa_ate_sentiment_pipeline_en_5.5.1_3.0_1731314099373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_absa_ate_sentiment_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_absa_ate_sentiment_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_absa_ate_sentiment_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|451.2 MB| + +## References + +https://huggingface.co/gauneg/roberta-base-absa-ate-sentiment + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_base_ainu_sayula_popoluca_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_ainu_sayula_popoluca_en.md new file mode 100644 index 00000000000000..17557ced9a6887 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_ainu_sayula_popoluca_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_ainu_sayula_popoluca RoBertaForTokenClassification from aynumosir +author: John Snow Labs +name: roberta_base_ainu_sayula_popoluca +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ainu_sayula_popoluca` is a English model originally trained by aynumosir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ainu_sayula_popoluca_en_5.5.1_3.0_1731311703241.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ainu_sayula_popoluca_en_5.5.1_3.0_1731311703241.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_ainu_sayula_popoluca","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_ainu_sayula_popoluca", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_ainu_sayula_popoluca| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|465.1 MB| + +## References + +https://huggingface.co/aynumosir/roberta-base-ainu-pos \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_base_ainu_sayula_popoluca_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_ainu_sayula_popoluca_pipeline_en.md new file mode 100644 index 00000000000000..5efb43e0ba2dbc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_ainu_sayula_popoluca_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_ainu_sayula_popoluca_pipeline pipeline RoBertaForTokenClassification from aynumosir +author: John Snow Labs +name: roberta_base_ainu_sayula_popoluca_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_ainu_sayula_popoluca_pipeline` is a English model originally trained by aynumosir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_ainu_sayula_popoluca_pipeline_en_5.5.1_3.0_1731311731304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_ainu_sayula_popoluca_pipeline_en_5.5.1_3.0_1731311731304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_ainu_sayula_popoluca_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_ainu_sayula_popoluca_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_ainu_sayula_popoluca_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.2 MB| + +## References + +https://huggingface.co/aynumosir/roberta-base-ainu-pos + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_base_bne_capitel_ner_bsc_lt_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_bne_capitel_ner_bsc_lt_pipeline_es.md new file mode 100644 index 00000000000000..1a463d8182f2f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_bne_capitel_ner_bsc_lt_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish roberta_base_bne_capitel_ner_bsc_lt_pipeline pipeline RoBertaForTokenClassification from BSC-LT +author: John Snow Labs +name: roberta_base_bne_capitel_ner_bsc_lt_pipeline +date: 2024-11-11 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_capitel_ner_bsc_lt_pipeline` is a Castilian, Spanish model originally trained by BSC-LT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_capitel_ner_bsc_lt_pipeline_es_5.5.1_3.0_1731311863930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_capitel_ner_bsc_lt_pipeline_es_5.5.1_3.0_1731311863930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_bne_capitel_ner_bsc_lt_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_bne_capitel_ner_bsc_lt_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_bne_capitel_ner_bsc_lt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|456.6 MB| + +## References + +https://huggingface.co/BSC-LT/roberta-base-bne-capitel-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_base_bne_capitel_ner_plantl_gob_es_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_bne_capitel_ner_plantl_gob_es_pipeline_es.md new file mode 100644 index 00000000000000..0b105e39847a7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_bne_capitel_ner_plantl_gob_es_pipeline_es.md @@ -0,0 +1,72 @@ +--- +layout: model +title: Castilian, Spanish roberta_base_bne_capitel_ner_plantl_gob_es_pipeline pipeline RoBertaForTokenClassification from PlanTL-GOB-ES +author: John Snow Labs +name: roberta_base_bne_capitel_ner_plantl_gob_es_pipeline +date: 2024-11-11 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_bne_capitel_ner_plantl_gob_es_pipeline` is a Castilian, Spanish model originally trained by PlanTL-GOB-ES. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_bne_capitel_ner_plantl_gob_es_pipeline_es_5.5.1_3.0_1731312026562.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_bne_capitel_ner_plantl_gob_es_pipeline_es_5.5.1_3.0_1731312026562.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("roberta_base_bne_capitel_ner_plantl_gob_es_pipeline", lang = "es") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("roberta_base_bne_capitel_ner_plantl_gob_es_pipeline", lang = "es") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_bne_capitel_ner_plantl_gob_es_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|456.6 MB| + +## References + +References + +https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne-capitel-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_base_finetuned_ner_cadec_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_finetuned_ner_cadec_en.md new file mode 100644 index 00000000000000..3a97f521081872 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_finetuned_ner_cadec_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_base_finetuned_ner_cadec RoBertaForTokenClassification from csNoHug +author: John Snow Labs +name: roberta_base_finetuned_ner_cadec +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_ner_cadec` is a English model originally trained by csNoHug. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_cadec_en_5.5.1_3.0_1731311612890.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_cadec_en_5.5.1_3.0_1731311612890.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_finetuned_ner_cadec","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_base_finetuned_ner_cadec", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_finetuned_ner_cadec| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|427.6 MB| + +## References + +https://huggingface.co/csNoHug/roberta-base-finetuned-ner-cadec \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_base_finetuned_ner_cadec_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_finetuned_ner_cadec_pipeline_en.md new file mode 100644 index 00000000000000..a7e5ebcab8f6d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_base_finetuned_ner_cadec_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_base_finetuned_ner_cadec_pipeline pipeline RoBertaForTokenClassification from csNoHug +author: John Snow Labs +name: roberta_base_finetuned_ner_cadec_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_finetuned_ner_cadec_pipeline` is a English model originally trained by csNoHug. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_cadec_pipeline_en_5.5.1_3.0_1731311647637.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_finetuned_ner_cadec_pipeline_en_5.5.1_3.0_1731311647637.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_base_finetuned_ner_cadec_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_base_finetuned_ner_cadec_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_finetuned_ner_cadec_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|427.6 MB| + +## References + +https://huggingface.co/csNoHug/roberta-base-finetuned-ner-cadec + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_epoch_7_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_epoch_7_en.md new file mode 100644 index 00000000000000..3100b75a89a3df --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_epoch_7_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_combined_generated_epoch_7 RoBertaForTokenClassification from ICT2214Team7 +author: John Snow Labs +name: roberta_combined_generated_epoch_7 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_epoch_7` is a English model originally trained by ICT2214Team7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_epoch_7_en_5.5.1_3.0_1731314414899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_epoch_7_en_5.5.1_3.0_1731314414899.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_epoch_7","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_epoch_7", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_combined_generated_epoch_7| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|306.6 MB| + +## References + +https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_epoch_7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_epoch_7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_epoch_7_pipeline_en.md new file mode 100644 index 00000000000000..8e90885accfe79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_epoch_7_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_combined_generated_epoch_7_pipeline pipeline RoBertaForTokenClassification from ICT2214Team7 +author: John Snow Labs +name: roberta_combined_generated_epoch_7_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_epoch_7_pipeline` is a English model originally trained by ICT2214Team7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_epoch_7_pipeline_en_5.5.1_3.0_1731314430537.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_epoch_7_pipeline_en_5.5.1_3.0_1731314430537.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_combined_generated_epoch_7_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_combined_generated_epoch_7_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_combined_generated_epoch_7_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.6 MB| + +## References + +https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_epoch_7 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_7_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_7_en.md new file mode 100644 index 00000000000000..1a06a4181992fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_7_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_combined_generated_v1_1_epoch_7 RoBertaForTokenClassification from ICT2214Team7 +author: John Snow Labs +name: roberta_combined_generated_v1_1_epoch_7 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_v1_1_epoch_7` is a English model originally trained by ICT2214Team7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_7_en_5.5.1_3.0_1731311705278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_7_en_5.5.1_3.0_1731311705278.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_v1_1_epoch_7","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_v1_1_epoch_7", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_combined_generated_v1_1_epoch_7| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|306.6 MB| + +## References + +https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_v1.1_epoch_7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_7_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_7_pipeline_en.md new file mode 100644 index 00000000000000..8b4b7edb97fc5d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_7_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_combined_generated_v1_1_epoch_7_pipeline pipeline RoBertaForTokenClassification from ICT2214Team7 +author: John Snow Labs +name: roberta_combined_generated_v1_1_epoch_7_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_v1_1_epoch_7_pipeline` is a English model originally trained by ICT2214Team7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_7_pipeline_en_5.5.1_3.0_1731311730183.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_7_pipeline_en_5.5.1_3.0_1731311730183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_combined_generated_v1_1_epoch_7_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_combined_generated_v1_1_epoch_7_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_combined_generated_v1_1_epoch_7_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.6 MB| + +## References + +https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_v1.1_epoch_7 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_8_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_8_en.md new file mode 100644 index 00000000000000..76dc29c3142f32 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_8_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_combined_generated_v1_1_epoch_8 RoBertaForTokenClassification from ICT2214Team7 +author: John Snow Labs +name: roberta_combined_generated_v1_1_epoch_8 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_v1_1_epoch_8` is a English model originally trained by ICT2214Team7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_8_en_5.5.1_3.0_1731311211090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_8_en_5.5.1_3.0_1731311211090.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_v1_1_epoch_8","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_combined_generated_v1_1_epoch_8", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_combined_generated_v1_1_epoch_8| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|306.6 MB| + +## References + +https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_v1.1_epoch_8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_8_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_8_pipeline_en.md new file mode 100644 index 00000000000000..37ebbef94efbad --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_combined_generated_v1_1_epoch_8_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_combined_generated_v1_1_epoch_8_pipeline pipeline RoBertaForTokenClassification from ICT2214Team7 +author: John Snow Labs +name: roberta_combined_generated_v1_1_epoch_8_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_combined_generated_v1_1_epoch_8_pipeline` is a English model originally trained by ICT2214Team7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_8_pipeline_en_5.5.1_3.0_1731311229047.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_combined_generated_v1_1_epoch_8_pipeline_en_5.5.1_3.0_1731311229047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_combined_generated_v1_1_epoch_8_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_combined_generated_v1_1_epoch_8_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_combined_generated_v1_1_epoch_8_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.6 MB| + +## References + +https://huggingface.co/ICT2214Team7/RoBERTa_Combined_Generated_v1.1_epoch_8 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_bajanthrimadhu_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_bajanthrimadhu_en.md new file mode 100644 index 00000000000000..1e374b19c60ac7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_bajanthrimadhu_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_bajanthrimadhu RoBertaForQuestionAnswering from BajanthriMadhu +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_bajanthrimadhu +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_bajanthrimadhu` is a English model originally trained by BajanthriMadhu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_bajanthrimadhu_en_5.5.1_3.0_1731291741389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_bajanthrimadhu_en_5.5.1_3.0_1731291741389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_bajanthrimadhu","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_bajanthrimadhu", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_bajanthrimadhu| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|463.5 MB| + +## References + +https://huggingface.co/BajanthriMadhu/roberta-finetuned-subjqa-movies_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline_en.md new file mode 100644 index 00000000000000..2b7aeb7039ec9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline pipeline RoBertaForQuestionAnswering from BajanthriMadhu +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline` is a English model originally trained by BajanthriMadhu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline_en_5.5.1_3.0_1731291765523.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline_en_5.5.1_3.0_1731291765523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_bajanthrimadhu_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|463.6 MB| + +## References + +https://huggingface.co/BajanthriMadhu/roberta-finetuned-subjqa-movies_2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_dcrowleymunster_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_dcrowleymunster_en.md new file mode 100644 index 00000000000000..a1b192f965294f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_dcrowleymunster_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_dcrowleymunster RoBertaForQuestionAnswering from dcrowleymunster +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_dcrowleymunster +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_dcrowleymunster` is a English model originally trained by dcrowleymunster. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_dcrowleymunster_en_5.5.1_3.0_1731291888611.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_dcrowleymunster_en_5.5.1_3.0_1731291888611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_dcrowleymunster","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_dcrowleymunster", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_dcrowleymunster| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/dcrowleymunster/roberta-finetuned-subjqa-movies_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline_en.md new file mode 100644 index 00000000000000..bea64e2b984f4f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline pipeline RoBertaForQuestionAnswering from dcrowleymunster +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline` is a English model originally trained by dcrowleymunster. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline_en_5.5.1_3.0_1731291912750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline_en_5.5.1_3.0_1731291912750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_dcrowleymunster_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/dcrowleymunster/roberta-finetuned-subjqa-movies_2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_moussamoustapha_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_moussamoustapha_en.md new file mode 100644 index 00000000000000..12ab1e5928ca39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_moussamoustapha_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_moussamoustapha RoBertaForQuestionAnswering from MoussaMoustapha +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_moussamoustapha +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, roberta] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_moussamoustapha` is a English model originally trained by MoussaMoustapha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_moussamoustapha_en_5.5.1_3.0_1731291906700.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_moussamoustapha_en_5.5.1_3.0_1731291906700.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_moussamoustapha","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_finetuned_subjqa_movies_2_moussamoustapha", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_moussamoustapha| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/MoussaMoustapha/roberta-finetuned-subjqa-movies_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline_en.md new file mode 100644 index 00000000000000..c008e8e13c60d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline pipeline RoBertaForQuestionAnswering from MoussaMoustapha +author: John Snow Labs +name: roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline` is a English model originally trained by MoussaMoustapha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline_en_5.5.1_3.0_1731291930779.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline_en_5.5.1_3.0_1731291930779.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_finetuned_subjqa_movies_2_moussamoustapha_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/MoussaMoustapha/roberta-finetuned-subjqa-movies_2 + +## Included Models + +- MultiDocumentAssembler +- RoBertaForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_abbr_filtered_plod_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_abbr_filtered_plod_en.md new file mode 100644 index 00000000000000..5e7ed41bcfe692 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_abbr_filtered_plod_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_finetuned_abbr_filtered_plod RoBertaForTokenClassification from surrey-nlp +author: John Snow Labs +name: roberta_large_finetuned_abbr_filtered_plod +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_abbr_filtered_plod` is a English model originally trained by surrey-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_abbr_filtered_plod_en_5.5.1_3.0_1731311931491.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_abbr_filtered_plod_en_5.5.1_3.0_1731311931491.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_finetuned_abbr_filtered_plod","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_finetuned_abbr_filtered_plod", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_finetuned_abbr_filtered_plod| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/surrey-nlp/roberta-large-finetuned-abbr-filtered-plod \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_ner_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_ner_finetuned_ner_en.md new file mode 100644 index 00000000000000..e0462a49903f4d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_ner_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_large_finetuned_ner_finetuned_ner RoBertaForTokenClassification from EngTig +author: John Snow Labs +name: roberta_large_finetuned_ner_finetuned_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_ner_finetuned_ner` is a English model originally trained by EngTig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_ner_finetuned_ner_en_5.5.1_3.0_1731314705749.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_ner_finetuned_ner_en_5.5.1_3.0_1731314705749.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_finetuned_ner_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_large_finetuned_ner_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_finetuned_ner_finetuned_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/EngTig/roberta-large-finetuned-ner-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_ner_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_ner_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..2f468654123ec1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_large_finetuned_ner_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_large_finetuned_ner_finetuned_ner_pipeline pipeline RoBertaForTokenClassification from EngTig +author: John Snow Labs +name: roberta_large_finetuned_ner_finetuned_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_finetuned_ner_finetuned_ner_pipeline` is a English model originally trained by EngTig. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_ner_finetuned_ner_pipeline_en_5.5.1_3.0_1731314773896.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_finetuned_ner_finetuned_ner_pipeline_en_5.5.1_3.0_1731314773896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_finetuned_ner_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_finetuned_ner_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_finetuned_ner_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/EngTig/roberta-large-finetuned-ner-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_large_lemon_spell_5k_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_large_lemon_spell_5k_pipeline_en.md new file mode 100644 index 00000000000000..4e6b72c0baef7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_large_lemon_spell_5k_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_large_lemon_spell_5k_pipeline pipeline RoBertaForTokenClassification from manred1997 +author: John Snow Labs +name: roberta_large_lemon_spell_5k_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_large_lemon_spell_5k_pipeline` is a English model originally trained by manred1997. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_large_lemon_spell_5k_pipeline_en_5.5.1_3.0_1731311835916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_large_lemon_spell_5k_pipeline_en_5.5.1_3.0_1731311835916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_large_lemon_spell_5k_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_large_lemon_spell_5k_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_large_lemon_spell_5k_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/manred1997/roberta-large_lemon-spell_5k + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_spanish_clinical_trials_neg_spec_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_spanish_clinical_trials_neg_spec_ner_en.md new file mode 100644 index 00000000000000..b2f5d749d07255 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_spanish_clinical_trials_neg_spec_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_spanish_clinical_trials_neg_spec_ner RoBertaForTokenClassification from medspaner +author: John Snow Labs +name: roberta_spanish_clinical_trials_neg_spec_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_spanish_clinical_trials_neg_spec_ner` is a English model originally trained by medspaner. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_spanish_clinical_trials_neg_spec_ner_en_5.5.1_3.0_1731314639240.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_spanish_clinical_trials_neg_spec_ner_en_5.5.1_3.0_1731314639240.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_spanish_clinical_trials_neg_spec_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_spanish_clinical_trials_neg_spec_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_spanish_clinical_trials_neg_spec_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|450.7 MB| + +## References + +https://huggingface.co/medspaner/roberta-es-clinical-trials-neg-spec-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_test_training_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_test_training_en.md new file mode 100644 index 00000000000000..a2add6cf1f0a02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_test_training_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English roberta_test_training RoBertaForTokenClassification from ICT2214Team7 +author: John Snow Labs +name: roberta_test_training +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_test_training` is a English model originally trained by ICT2214Team7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_test_training_en_5.5.1_3.0_1731311877878.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_test_training_en_5.5.1_3.0_1731311877878.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_test_training","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("roberta_test_training", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_test_training| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|306.5 MB| + +## References + +https://huggingface.co/ICT2214Team7/RoBERTa_Test_Training \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-roberta_test_training_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-roberta_test_training_pipeline_en.md new file mode 100644 index 00000000000000..d66dbdcc87894b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-roberta_test_training_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English roberta_test_training_pipeline pipeline RoBertaForTokenClassification from ICT2214Team7 +author: John Snow Labs +name: roberta_test_training_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_test_training_pipeline` is a English model originally trained by ICT2214Team7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_test_training_pipeline_en_5.5.1_3.0_1731311894107.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_test_training_pipeline_en_5.5.1_3.0_1731311894107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("roberta_test_training_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("roberta_test_training_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_test_training_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|306.6 MB| + +## References + +https://huggingface.co/ICT2214Team7/RoBERTa_Test_Training + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-rubert_finetuned_squad_en.md b/docs/_posts/ahmedlone127/2024-11-11-rubert_finetuned_squad_en.md new file mode 100644 index 00000000000000..e5c3d1be04bc2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-rubert_finetuned_squad_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English rubert_finetuned_squad BertForQuestionAnswering from sad-bkt +author: John Snow Labs +name: rubert_finetuned_squad +date: 2024-11-11 +tags: [en, open_source, onnx, question_answering, bert] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +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.`rubert_finetuned_squad` is a English model originally trained by sad-bkt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_finetuned_squad_en_5.5.1_3.0_1731288820745.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_finetuned_squad_en_5.5.1_3.0_1731288820745.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("rubert_finetuned_squad","en") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("rubert_finetuned_squad", "en") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_finetuned_squad| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|en| +|Size:|664.3 MB| + +## References + +https://huggingface.co/sad-bkt/rubert-finetuned-squad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-rubert_finetuned_squad_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-rubert_finetuned_squad_pipeline_en.md new file mode 100644 index 00000000000000..20919abae61627 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-rubert_finetuned_squad_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English rubert_finetuned_squad_pipeline pipeline BertForQuestionAnswering from sad-bkt +author: John Snow Labs +name: rubert_finetuned_squad_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Question Answering +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_finetuned_squad_pipeline` is a English model originally trained by sad-bkt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_finetuned_squad_pipeline_en_5.5.1_3.0_1731288867678.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_finetuned_squad_pipeline_en_5.5.1_3.0_1731288867678.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rubert_finetuned_squad_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rubert_finetuned_squad_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_finetuned_squad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|664.3 MB| + +## References + +https://huggingface.co/sad-bkt/rubert-finetuned-squad + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-rubert_russian_qa_sberquad_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-11-11-rubert_russian_qa_sberquad_pipeline_ru.md new file mode 100644 index 00000000000000..f87c9c44b4e02a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-rubert_russian_qa_sberquad_pipeline_ru.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Russian rubert_russian_qa_sberquad_pipeline pipeline BertForQuestionAnswering from milyausha2801 +author: John Snow Labs +name: rubert_russian_qa_sberquad_pipeline +date: 2024-11-11 +tags: [ru, open_source, pipeline, onnx] +task: Question Answering +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForQuestionAnswering, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_russian_qa_sberquad_pipeline` is a Russian model originally trained by milyausha2801. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_russian_qa_sberquad_pipeline_ru_5.5.1_3.0_1731289278063.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_russian_qa_sberquad_pipeline_ru_5.5.1_3.0_1731289278063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rubert_russian_qa_sberquad_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rubert_russian_qa_sberquad_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_russian_qa_sberquad_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|664.3 MB| + +## References + +https://huggingface.co/milyausha2801/rubert-russian-qa-sberquad + +## Included Models + +- MultiDocumentAssembler +- BertForQuestionAnswering \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-rubert_russian_qa_sberquad_ru.md b/docs/_posts/ahmedlone127/2024-11-11-rubert_russian_qa_sberquad_ru.md new file mode 100644 index 00000000000000..e86419e4db3e19 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-rubert_russian_qa_sberquad_ru.md @@ -0,0 +1,86 @@ +--- +layout: model +title: Russian rubert_russian_qa_sberquad BertForQuestionAnswering from milyausha2801 +author: John Snow Labs +name: rubert_russian_qa_sberquad +date: 2024-11-11 +tags: [ru, open_source, onnx, question_answering, bert] +task: Question Answering +language: ru +edition: Spark NLP 5.5.1 +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.`rubert_russian_qa_sberquad` is a Russian model originally trained by milyausha2801. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_russian_qa_sberquad_ru_5.5.1_3.0_1731289240932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_russian_qa_sberquad_ru_5.5.1_3.0_1731289240932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +documentAssembler = MultiDocumentAssembler() \ + .setInputCol(["question", "context"]) \ + .setOutputCol(["document_question", "document_context"]) + +spanClassifier = BertForQuestionAnswering.pretrained("rubert_russian_qa_sberquad","ru") \ + .setInputCols(["document_question","document_context"]) \ + .setOutputCol("answer") + +pipeline = Pipeline().setStages([documentAssembler, spanClassifier]) +data = spark.createDataFrame([["What framework do I use?","I use spark-nlp."]]).toDF("document_question", "document_context") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new MultiDocumentAssembler() + .setInputCol(Array("question", "context")) + .setOutputCol(Array("document_question", "document_context")) + +val spanClassifier = BertForQuestionAnswering.pretrained("rubert_russian_qa_sberquad", "ru") + .setInputCols(Array("document_question","document_context")) + .setOutputCol("answer") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier)) +val data = Seq("What framework do I use?","I use spark-nlp.").toDS.toDF("document_question", "document_context") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_russian_qa_sberquad| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document_question, document_context]| +|Output Labels:|[answer]| +|Language:|ru| +|Size:|664.3 MB| + +## References + +https://huggingface.co/milyausha2801/rubert-russian-qa-sberquad \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-rupunct_small_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-11-11-rupunct_small_pipeline_ru.md new file mode 100644 index 00000000000000..990b9ad591fd02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-rupunct_small_pipeline_ru.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Russian rupunct_small_pipeline pipeline BertForTokenClassification from RUPunct +author: John Snow Labs +name: rupunct_small_pipeline +date: 2024-11-11 +tags: [ru, open_source, pipeline, onnx] +task: Named Entity Recognition +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rupunct_small_pipeline` is a Russian model originally trained by RUPunct. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rupunct_small_pipeline_ru_5.5.1_3.0_1731299090139.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rupunct_small_pipeline_ru_5.5.1_3.0_1731299090139.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("rupunct_small_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("rupunct_small_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rupunct_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|109.2 MB| + +## References + +https://huggingface.co/RUPunct/RUPunct_small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-rupunct_small_ru.md b/docs/_posts/ahmedlone127/2024-11-11-rupunct_small_ru.md new file mode 100644 index 00000000000000..8e85fe7ceb62b0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-rupunct_small_ru.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Russian rupunct_small BertForTokenClassification from RUPunct +author: John Snow Labs +name: rupunct_small +date: 2024-11-11 +tags: [ru, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rupunct_small` is a Russian model originally trained by RUPunct. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rupunct_small_ru_5.5.1_3.0_1731299084262.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rupunct_small_ru_5.5.1_3.0_1731299084262.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') + +tokenClassifier = BertForTokenClassification.pretrained("rupunct_small","ru") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("rupunct_small", "ru") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rupunct_small| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ru| +|Size:|109.2 MB| + +## References + +https://huggingface.co/RUPunct/RUPunct_small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ruroberta_large_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-ruroberta_large_ner_en.md new file mode 100644 index 00000000000000..3bb5724da55871 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ruroberta_large_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English ruroberta_large_ner RoBertaForTokenClassification from KobanBanan +author: John Snow Labs +name: ruroberta_large_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ruroberta_large_ner` is a English model originally trained by KobanBanan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ruroberta_large_ner_en_5.5.1_3.0_1731314157839.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ruroberta_large_ner_en_5.5.1_3.0_1731314157839.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("ruroberta_large_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("ruroberta_large_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ruroberta_large_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/KobanBanan/ruRoberta-large_ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-ruroberta_large_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-ruroberta_large_ner_pipeline_en.md new file mode 100644 index 00000000000000..9cf3826d7590c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-ruroberta_large_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English ruroberta_large_ner_pipeline pipeline RoBertaForTokenClassification from KobanBanan +author: John Snow Labs +name: ruroberta_large_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ruroberta_large_ner_pipeline` is a English model originally trained by KobanBanan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ruroberta_large_ner_pipeline_en_5.5.1_3.0_1731314229337.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ruroberta_large_ner_pipeline_en_5.5.1_3.0_1731314229337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("ruroberta_large_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("ruroberta_large_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ruroberta_large_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/KobanBanan/ruRoberta-large_ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-scenario_nepal_bhasa_en.md b/docs/_posts/ahmedlone127/2024-11-11-scenario_nepal_bhasa_en.md new file mode 100644 index 00000000000000..c7093e0b973f82 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-scenario_nepal_bhasa_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English scenario_nepal_bhasa BertForSequenceClassification from Mahmoud3899 +author: John Snow Labs +name: scenario_nepal_bhasa +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_nepal_bhasa` is a English model originally trained by Mahmoud3899. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_nepal_bhasa_en_5.5.1_3.0_1731310227574.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_nepal_bhasa_en_5.5.1_3.0_1731310227574.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("scenario_nepal_bhasa","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scenario_nepal_bhasa", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_nepal_bhasa| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Mahmoud3899/scenario_new \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-scenario_nepal_bhasa_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-scenario_nepal_bhasa_pipeline_en.md new file mode 100644 index 00000000000000..659b60d1e70c3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-scenario_nepal_bhasa_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English scenario_nepal_bhasa_pipeline pipeline BertForSequenceClassification from Mahmoud3899 +author: John Snow Labs +name: scenario_nepal_bhasa_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scenario_nepal_bhasa_pipeline` is a English model originally trained by Mahmoud3899. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scenario_nepal_bhasa_pipeline_en_5.5.1_3.0_1731310249022.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scenario_nepal_bhasa_pipeline_en_5.5.1_3.0_1731310249022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("scenario_nepal_bhasa_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("scenario_nepal_bhasa_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scenario_nepal_bhasa_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Mahmoud3899/scenario_new + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-screenshot_fashion_clip_finetuned_en.md b/docs/_posts/ahmedlone127/2024-11-11-screenshot_fashion_clip_finetuned_en.md new file mode 100644 index 00000000000000..ed8c1582e10d65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-screenshot_fashion_clip_finetuned_en.md @@ -0,0 +1,120 @@ +--- +layout: model +title: English screenshot_fashion_clip_finetuned CLIPForZeroShotClassification from justin-shopcapsule +author: John Snow Labs +name: screenshot_fashion_clip_finetuned +date: 2024-11-11 +tags: [en, open_source, onnx, zero_shot, clip, image] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: CLIPForZeroShotClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`screenshot_fashion_clip_finetuned` is a English model originally trained by justin-shopcapsule. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/screenshot_fashion_clip_finetuned_en_5.5.1_3.0_1731287543136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/screenshot_fashion_clip_finetuned_en_5.5.1_3.0_1731287543136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +imageDF = spark.read \ + .format("image") \ + .option("dropInvalid", value = True) \ + .load("src/test/resources/image/") + +candidateLabels = [ + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox"] + +ImageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") + +imageClassifier = CLIPForZeroShotClassification.pretrained("screenshot_fashion_clip_finetuned","en") \ + .setInputCols(["image_assembler"]) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +pipeline = Pipeline().setStages([ImageAssembler, imageClassifier]) +pipelineModel = pipeline.fit(imageDF) +pipelineDF = pipelineModel.transform(imageDF) + + +``` +```scala + + +val imageDF = ResourceHelper.spark.read + .format("image") + .option("dropInvalid", value = true) + .load("src/test/resources/image/") + +val candidateLabels = Array( + "a photo of a bird", + "a photo of a cat", + "a photo of a dog", + "a photo of a hen", + "a photo of a hippo", + "a photo of a room", + "a photo of a tractor", + "a photo of an ostrich", + "a photo of an ox") + +val imageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val imageClassifier = CLIPForZeroShotClassification.pretrained("screenshot_fashion_clip_finetuned","en") \ + .setInputCols(Array("image_assembler")) \ + .setOutputCol("label") \ + .setCandidateLabels(candidateLabels) + +val pipeline = new Pipeline().setStages(Array(imageAssembler, imageClassifier)) +val pipelineModel = pipeline.fit(imageDF) +val pipelineDF = pipelineModel.transform(imageDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|screenshot_fashion_clip_finetuned| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[image_assembler]| +|Output Labels:|[label]| +|Language:|en| +|Size:|567.5 MB| + +## References + +https://huggingface.co/justin-shopcapsule/screenshot-fashion-clip-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-screenshot_fashion_clip_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-screenshot_fashion_clip_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..102d8b6c14a858 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-screenshot_fashion_clip_finetuned_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English screenshot_fashion_clip_finetuned_pipeline pipeline CLIPForZeroShotClassification from justin-shopcapsule +author: John Snow Labs +name: screenshot_fashion_clip_finetuned_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Zero-Shot Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained CLIPForZeroShotClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`screenshot_fashion_clip_finetuned_pipeline` is a English model originally trained by justin-shopcapsule. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/screenshot_fashion_clip_finetuned_pipeline_en_5.5.1_3.0_1731287572581.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/screenshot_fashion_clip_finetuned_pipeline_en_5.5.1_3.0_1731287572581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("screenshot_fashion_clip_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("screenshot_fashion_clip_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|screenshot_fashion_clip_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|567.6 MB| + +## References + +https://huggingface.co/justin-shopcapsule/screenshot-fashion-clip-finetuned + +## Included Models + +- ImageAssembler +- CLIPForZeroShotClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-securebert_finetuned_ner_en.md b/docs/_posts/ahmedlone127/2024-11-11-securebert_finetuned_ner_en.md new file mode 100644 index 00000000000000..1b411577d74f8c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-securebert_finetuned_ner_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English securebert_finetuned_ner RoBertaForTokenClassification from zohreaz +author: John Snow Labs +name: securebert_finetuned_ner +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: RoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_finetuned_ner` is a English model originally trained by zohreaz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_finetuned_ner_en_5.5.1_3.0_1731311208086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_finetuned_ner_en_5.5.1_3.0_1731311208086.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') + +tokenClassifier = RoBertaForTokenClassification.pretrained("securebert_finetuned_ner","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = RoBertaForTokenClassification.pretrained("securebert_finetuned_ner", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|securebert_finetuned_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|466.4 MB| + +## References + +https://huggingface.co/zohreaz/SecureBERT-finetuned-ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-securebert_finetuned_ner_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-securebert_finetuned_ner_pipeline_en.md new file mode 100644 index 00000000000000..2b9c4fceb757e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-securebert_finetuned_ner_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English securebert_finetuned_ner_pipeline pipeline RoBertaForTokenClassification from zohreaz +author: John Snow Labs +name: securebert_finetuned_ner_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained RoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`securebert_finetuned_ner_pipeline` is a English model originally trained by zohreaz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/securebert_finetuned_ner_pipeline_en_5.5.1_3.0_1731311234765.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/securebert_finetuned_ner_pipeline_en_5.5.1_3.0_1731311234765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("securebert_finetuned_ner_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("securebert_finetuned_ner_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|securebert_finetuned_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|466.4 MB| + +## References + +https://huggingface.co/zohreaz/SecureBERT-finetuned-ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- RoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_7_epoch_edu_model_finetuned_fintech_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_7_epoch_edu_model_finetuned_fintech_en.md new file mode 100644 index 00000000000000..42a54be53d2e4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_7_epoch_edu_model_finetuned_fintech_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_7_epoch_edu_model_finetuned_fintech BertSentenceEmbeddings from Pastushoc +author: John Snow Labs +name: sent_7_epoch_edu_model_finetuned_fintech +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_7_epoch_edu_model_finetuned_fintech` is a English model originally trained by Pastushoc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_7_epoch_edu_model_finetuned_fintech_en_5.5.1_3.0_1731295684263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_7_epoch_edu_model_finetuned_fintech_en_5.5.1_3.0_1731295684263.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_7_epoch_edu_model_finetuned_fintech","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_7_epoch_edu_model_finetuned_fintech","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_7_epoch_edu_model_finetuned_fintech| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|108.7 MB| + +## References + +https://huggingface.co/Pastushoc/7_epoch_edu_model-finetuned-fintech \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_7_epoch_edu_model_finetuned_fintech_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_7_epoch_edu_model_finetuned_fintech_pipeline_en.md new file mode 100644 index 00000000000000..5e2b17bccd2d2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_7_epoch_edu_model_finetuned_fintech_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_7_epoch_edu_model_finetuned_fintech_pipeline pipeline BertSentenceEmbeddings from Pastushoc +author: John Snow Labs +name: sent_7_epoch_edu_model_finetuned_fintech_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_7_epoch_edu_model_finetuned_fintech_pipeline` is a English model originally trained by Pastushoc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_7_epoch_edu_model_finetuned_fintech_pipeline_en_5.5.1_3.0_1731295690134.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_7_epoch_edu_model_finetuned_fintech_pipeline_en_5.5.1_3.0_1731295690134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_7_epoch_edu_model_finetuned_fintech_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_7_epoch_edu_model_finetuned_fintech_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_7_epoch_edu_model_finetuned_fintech_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|109.3 MB| + +## References + +https://huggingface.co/Pastushoc/7_epoch_edu_model-finetuned-fintech + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_bert_base_english_french_arabic_cased_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_base_english_french_arabic_cased_en.md new file mode 100644 index 00000000000000..596ef115ca3bfe --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_base_english_french_arabic_cased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_base_english_french_arabic_cased BertSentenceEmbeddings from Geotrend +author: John Snow Labs +name: sent_bert_base_english_french_arabic_cased +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_english_french_arabic_cased` is a English model originally trained by Geotrend. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_arabic_cased_en_5.5.1_3.0_1731296029932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_arabic_cased_en_5.5.1_3.0_1731296029932.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_english_french_arabic_cased","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_base_english_french_arabic_cased","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_english_french_arabic_cased| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|426.0 MB| + +## References + +https://huggingface.co/Geotrend/bert-base-en-fr-ar-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_bert_base_english_french_arabic_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_base_english_french_arabic_cased_pipeline_en.md new file mode 100644 index 00000000000000..d3aaf7c6ebedb1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_base_english_french_arabic_cased_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bert_base_english_french_arabic_cased_pipeline pipeline BertSentenceEmbeddings from Geotrend +author: John Snow Labs +name: sent_bert_base_english_french_arabic_cased_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_base_english_french_arabic_cased_pipeline` is a English model originally trained by Geotrend. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_arabic_cased_pipeline_en_5.5.1_3.0_1731296051698.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_base_english_french_arabic_cased_pipeline_en_5.5.1_3.0_1731296051698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_base_english_french_arabic_cased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_base_english_french_arabic_cased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_base_english_french_arabic_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|426.6 MB| + +## References + +https://huggingface.co/Geotrend/bert-base-en-fr-ar-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_bert_large_cased_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_large_cased_en.md new file mode 100644 index 00000000000000..6256a2727669dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_large_cased_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: BERT Sentence Embeddings (Large Cased) +author: John Snow Labs +name: sent_bert_large_cased +date: 2024-11-11 +tags: [open_source, embeddings, en, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +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/sent_bert_large_cased_en_5.5.1_3.0_1731295875935.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_en_5.5.1_3.0_1731295875935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +... +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_cased", "en") \ +.setInputCols("sentence") \ +.setOutputCol("sentence_embeddings") +nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, embeddings]) +pipeline_model = nlp_pipeline.fit(spark.createDataFrame([[""]]).toDF("text")) +result = pipeline_model.transform(spark.createDataFrame([['I hate cancer', "Antibiotics aren't painkiller"]], ["text"])) +``` +```scala +... +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_large_cased", "en") +.setInputCols("sentence") +.setOutputCol("sentence_embeddings") +val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, embeddings)) +val data = Seq("I hate cancer", "Antibiotics aren't painkiller").toDF("text") +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu + +text = ["I hate cancer", "Antibiotics aren't painkiller"] +embeddings_df = nlu.load('en.embed_sentence.bert_large_cased').predict(text, output_level='sentence') +embeddings_df +``` +
+ +## Results + +```bash + + + token en_embed_sentence_bert_large_cased_embeddings + + I [[-0.6228358149528503, -0.3453695774078369, 0.... +love [[-0.6228358149528503, -0.3453695774078369, 0.... +NLP [[-0.6228358149528503, -0.3453695774078369, 0.... +``` + +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_large_cased| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.2 GB| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_bert_large_cased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_large_cased_pipeline_en.md new file mode 100644 index 00000000000000..20f8f983a6fe25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_large_cased_pipeline_en.md @@ -0,0 +1,73 @@ +--- +layout: model +title: English sent_bert_large_cased_pipeline pipeline BertSentenceEmbeddings from google-bert +author: John Snow Labs +name: sent_bert_large_cased_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_large_cased_pipeline` is a English model originally trained by google-bert. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_pipeline_en_5.5.1_3.0_1731295939295.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_large_cased_pipeline_en_5.5.1_3.0_1731295939295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("sent_bert_large_cased_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("sent_bert_large_cased_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_large_cased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +References + +https://huggingface.co/google-bert/bert-large-cased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_bert_small_uncased_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_small_uncased_en.md new file mode 100644 index 00000000000000..396ecfa34b8088 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_small_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bert_small_uncased BertSentenceEmbeddings from gaunernst +author: John Snow Labs +name: sent_bert_small_uncased +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_uncased` is a English model originally trained by gaunernst. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_uncased_en_5.5.1_3.0_1731295492148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_uncased_en_5.5.1_3.0_1731295492148.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_uncased","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bert_small_uncased","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_small_uncased| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|107.0 MB| + +## References + +https://huggingface.co/gaunernst/bert-small-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_bert_small_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_small_uncased_pipeline_en.md new file mode 100644 index 00000000000000..41d9628eebb246 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_bert_small_uncased_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bert_small_uncased_pipeline pipeline BertSentenceEmbeddings from gaunernst +author: John Snow Labs +name: sent_bert_small_uncased_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bert_small_uncased_pipeline` is a English model originally trained by gaunernst. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bert_small_uncased_pipeline_en_5.5.1_3.0_1731295497059.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bert_small_uncased_pipeline_en_5.5.1_3.0_1731295497059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bert_small_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bert_small_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bert_small_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|107.5 MB| + +## References + +https://huggingface.co/gaunernst/bert-small-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_bowdpr_wiki_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_bowdpr_wiki_en.md new file mode 100644 index 00000000000000..7b4bff50cf0205 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_bowdpr_wiki_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_bowdpr_wiki BertSentenceEmbeddings from bowdpr +author: John Snow Labs +name: sent_bowdpr_wiki +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bowdpr_wiki` is a English model originally trained by bowdpr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bowdpr_wiki_en_5.5.1_3.0_1731295788052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bowdpr_wiki_en_5.5.1_3.0_1731295788052.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_bowdpr_wiki","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_bowdpr_wiki","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bowdpr_wiki| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.9 MB| + +## References + +https://huggingface.co/bowdpr/bowdpr_wiki \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_bowdpr_wiki_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_bowdpr_wiki_pipeline_en.md new file mode 100644 index 00000000000000..582cd91ff203ff --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_bowdpr_wiki_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_bowdpr_wiki_pipeline pipeline BertSentenceEmbeddings from bowdpr +author: John Snow Labs +name: sent_bowdpr_wiki_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_bowdpr_wiki_pipeline` is a English model originally trained by bowdpr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_bowdpr_wiki_pipeline_en_5.5.1_3.0_1731295808981.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_bowdpr_wiki_pipeline_en_5.5.1_3.0_1731295808981.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_bowdpr_wiki_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_bowdpr_wiki_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_bowdpr_wiki_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.5 MB| + +## References + +https://huggingface.co/bowdpr/bowdpr_wiki + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_cocodr_large_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_cocodr_large_en.md new file mode 100644 index 00000000000000..7caf59748d94eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_cocodr_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_cocodr_large BertSentenceEmbeddings from OpenMatch +author: John Snow Labs +name: sent_cocodr_large +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cocodr_large` is a English model originally trained by OpenMatch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_cocodr_large_en_5.5.1_3.0_1731296353493.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cocodr_large_en_5.5.1_3.0_1731296353493.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_cocodr_large","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_cocodr_large","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_cocodr_large| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/OpenMatch/cocodr-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_cocodr_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_cocodr_large_pipeline_en.md new file mode 100644 index 00000000000000..fdcc0429397e6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_cocodr_large_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_cocodr_large_pipeline pipeline BertSentenceEmbeddings from OpenMatch +author: John Snow Labs +name: sent_cocodr_large_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_cocodr_large_pipeline` is a English model originally trained by OpenMatch. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_cocodr_large_pipeline_en_5.5.1_3.0_1731296416055.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_cocodr_large_pipeline_en_5.5.1_3.0_1731296416055.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_cocodr_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_cocodr_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_cocodr_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/OpenMatch/cocodr-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_flang_spanbert_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_flang_spanbert_en.md new file mode 100644 index 00000000000000..00ffea7911dde4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_flang_spanbert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_flang_spanbert BertSentenceEmbeddings from SALT-NLP +author: John Snow Labs +name: sent_flang_spanbert +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_flang_spanbert` is a English model originally trained by SALT-NLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_flang_spanbert_en_5.5.1_3.0_1731295507910.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_flang_spanbert_en_5.5.1_3.0_1731295507910.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_flang_spanbert","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_flang_spanbert","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_flang_spanbert| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|403.6 MB| + +## References + +https://huggingface.co/SALT-NLP/FLANG-SpanBERT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_flang_spanbert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_flang_spanbert_pipeline_en.md new file mode 100644 index 00000000000000..3e59ffc19a4472 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_flang_spanbert_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_flang_spanbert_pipeline pipeline BertSentenceEmbeddings from SALT-NLP +author: John Snow Labs +name: sent_flang_spanbert_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_flang_spanbert_pipeline` is a English model originally trained by SALT-NLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_flang_spanbert_pipeline_en_5.5.1_3.0_1731295529427.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_flang_spanbert_pipeline_en_5.5.1_3.0_1731295529427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_flang_spanbert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_flang_spanbert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_flang_spanbert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|404.1 MB| + +## References + +https://huggingface.co/SALT-NLP/FLANG-SpanBERT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_gww_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_gww_en.md new file mode 100644 index 00000000000000..2cf6dab7b7a777 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_gww_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_gww BertSentenceEmbeddings from dunlp +author: John Snow Labs +name: sent_gww +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gww` is a English model originally trained by dunlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gww_en_5.5.1_3.0_1731296186768.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gww_en_5.5.1_3.0_1731296186768.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_gww","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_gww","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_gww| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/dunlp/GWW \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_gww_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_gww_pipeline_en.md new file mode 100644 index 00000000000000..c94c30884dffce --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_gww_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_gww_pipeline pipeline BertSentenceEmbeddings from dunlp +author: John Snow Labs +name: sent_gww_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_gww_pipeline` is a English model originally trained by dunlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_gww_pipeline_en_5.5.1_3.0_1731296207716.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_gww_pipeline_en_5.5.1_3.0_1731296207716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_gww_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_gww_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_gww_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.3 MB| + +## References + +https://huggingface.co/dunlp/GWW + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_hindi_tweets_bert_hateful_hi.md b/docs/_posts/ahmedlone127/2024-11-11-sent_hindi_tweets_bert_hateful_hi.md new file mode 100644 index 00000000000000..1206e880b00eb4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_hindi_tweets_bert_hateful_hi.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Hindi sent_hindi_tweets_bert_hateful BertSentenceEmbeddings from l3cube-pune +author: John Snow Labs +name: sent_hindi_tweets_bert_hateful +date: 2024-11-11 +tags: [hi, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: hi +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hindi_tweets_bert_hateful` is a Hindi model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hindi_tweets_bert_hateful_hi_5.5.1_3.0_1731295605957.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hindi_tweets_bert_hateful_hi_5.5.1_3.0_1731295605957.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_hindi_tweets_bert_hateful","hi") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_hindi_tweets_bert_hateful","hi") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_hindi_tweets_bert_hateful| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|hi| +|Size:|890.6 MB| + +## References + +https://huggingface.co/l3cube-pune/hindi-tweets-bert-hateful \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_hindi_tweets_bert_hateful_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-11-11-sent_hindi_tweets_bert_hateful_pipeline_hi.md new file mode 100644 index 00000000000000..b32d4fbe8decb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_hindi_tweets_bert_hateful_pipeline_hi.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Hindi sent_hindi_tweets_bert_hateful_pipeline pipeline BertSentenceEmbeddings from l3cube-pune +author: John Snow Labs +name: sent_hindi_tweets_bert_hateful_pipeline +date: 2024-11-11 +tags: [hi, open_source, pipeline, onnx] +task: Embeddings +language: hi +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hindi_tweets_bert_hateful_pipeline` is a Hindi model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hindi_tweets_bert_hateful_pipeline_hi_5.5.1_3.0_1731295656628.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hindi_tweets_bert_hateful_pipeline_hi_5.5.1_3.0_1731295656628.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_hindi_tweets_bert_hateful_pipeline", lang = "hi") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_hindi_tweets_bert_hateful_pipeline", lang = "hi") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_hindi_tweets_bert_hateful_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|891.2 MB| + +## References + +https://huggingface.co/l3cube-pune/hindi-tweets-bert-hateful + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_hinglish_bert_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_hinglish_bert_en.md new file mode 100644 index 00000000000000..0f0e6559c1ccfa --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_hinglish_bert_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_hinglish_bert BertSentenceEmbeddings from meghanabhange +author: John Snow Labs +name: sent_hinglish_bert +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hinglish_bert` is a English model originally trained by meghanabhange. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hinglish_bert_en_5.5.1_3.0_1731296141121.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hinglish_bert_en_5.5.1_3.0_1731296141121.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_hinglish_bert","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_hinglish_bert","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_hinglish_bert| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|665.0 MB| + +## References + +https://huggingface.co/meghanabhange/Hinglish-Bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_hinglish_bert_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_hinglish_bert_pipeline_en.md new file mode 100644 index 00000000000000..8bcbeff1e1404e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_hinglish_bert_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_hinglish_bert_pipeline pipeline BertSentenceEmbeddings from meghanabhange +author: John Snow Labs +name: sent_hinglish_bert_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_hinglish_bert_pipeline` is a English model originally trained by meghanabhange. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_hinglish_bert_pipeline_en_5.5.1_3.0_1731296175548.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_hinglish_bert_pipeline_en_5.5.1_3.0_1731296175548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_hinglish_bert_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_hinglish_bert_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_hinglish_bert_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|665.6 MB| + +## References + +https://huggingface.co/meghanabhange/Hinglish-Bert + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_kinyabert_small_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_kinyabert_small_en.md new file mode 100644 index 00000000000000..fa36e89fefb180 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_kinyabert_small_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_kinyabert_small BertSentenceEmbeddings from jean-paul +author: John Snow Labs +name: sent_kinyabert_small +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kinyabert_small` is a English model originally trained by jean-paul. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_en_5.5.1_3.0_1731296300457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_en_5.5.1_3.0_1731296300457.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_kinyabert_small","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_kinyabert_small","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_kinyabert_small| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|247.4 MB| + +## References + +https://huggingface.co/jean-paul/KinyaBERT-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_kinyabert_small_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_kinyabert_small_pipeline_en.md new file mode 100644 index 00000000000000..9357bf7410de47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_kinyabert_small_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_kinyabert_small_pipeline pipeline BertSentenceEmbeddings from jean-paul +author: John Snow Labs +name: sent_kinyabert_small_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_kinyabert_small_pipeline` is a English model originally trained by jean-paul. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_pipeline_en_5.5.1_3.0_1731296313640.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_kinyabert_small_pipeline_en_5.5.1_3.0_1731296313640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_kinyabert_small_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_kinyabert_small_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_kinyabert_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|248.0 MB| + +## References + +https://huggingface.co/jean-paul/KinyaBERT-small + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_legal_bert_base_uncased_finetuned_rramicus_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_legal_bert_base_uncased_finetuned_rramicus_en.md new file mode 100644 index 00000000000000..a2068c527f4a0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_legal_bert_base_uncased_finetuned_rramicus_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_legal_bert_base_uncased_finetuned_rramicus BertSentenceEmbeddings from repro-rights-amicus-briefs +author: John Snow Labs +name: sent_legal_bert_base_uncased_finetuned_rramicus +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_bert_base_uncased_finetuned_rramicus` is a English model originally trained by repro-rights-amicus-briefs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_bert_base_uncased_finetuned_rramicus_en_5.5.1_3.0_1731295609641.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_bert_base_uncased_finetuned_rramicus_en_5.5.1_3.0_1731295609641.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_legal_bert_base_uncased_finetuned_rramicus","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_legal_bert_base_uncased_finetuned_rramicus","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_legal_bert_base_uncased_finetuned_rramicus| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.1 MB| + +## References + +https://huggingface.co/repro-rights-amicus-briefs/legal-bert-base-uncased-finetuned-RRamicus \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_legal_bert_base_uncased_finetuned_rramicus_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_legal_bert_base_uncased_finetuned_rramicus_pipeline_en.md new file mode 100644 index 00000000000000..e1feaa3e7fff1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_legal_bert_base_uncased_finetuned_rramicus_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_legal_bert_base_uncased_finetuned_rramicus_pipeline pipeline BertSentenceEmbeddings from repro-rights-amicus-briefs +author: John Snow Labs +name: sent_legal_bert_base_uncased_finetuned_rramicus_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_legal_bert_base_uncased_finetuned_rramicus_pipeline` is a English model originally trained by repro-rights-amicus-briefs. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_legal_bert_base_uncased_finetuned_rramicus_pipeline_en_5.5.1_3.0_1731295639417.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_legal_bert_base_uncased_finetuned_rramicus_pipeline_en_5.5.1_3.0_1731295639417.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_legal_bert_base_uncased_finetuned_rramicus_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_legal_bert_base_uncased_finetuned_rramicus_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_legal_bert_base_uncased_finetuned_rramicus_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|407.6 MB| + +## References + +https://huggingface.co/repro-rights-amicus-briefs/legal-bert-base-uncased-finetuned-RRamicus + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_logion_50k_wordpiece_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_logion_50k_wordpiece_en.md new file mode 100644 index 00000000000000..16ef3a4bd3e8eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_logion_50k_wordpiece_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_logion_50k_wordpiece BertSentenceEmbeddings from cabrooks +author: John Snow Labs +name: sent_logion_50k_wordpiece +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_logion_50k_wordpiece` is a English model originally trained by cabrooks. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_logion_50k_wordpiece_en_5.5.1_3.0_1731296515126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_logion_50k_wordpiece_en_5.5.1_3.0_1731296515126.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_logion_50k_wordpiece","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_logion_50k_wordpiece","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_logion_50k_wordpiece| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|464.1 MB| + +## References + +https://huggingface.co/cabrooks/LOGION-50k_wordpiece \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_logion_50k_wordpiece_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_logion_50k_wordpiece_pipeline_en.md new file mode 100644 index 00000000000000..db875dd24d6509 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_logion_50k_wordpiece_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_logion_50k_wordpiece_pipeline pipeline BertSentenceEmbeddings from cabrooks +author: John Snow Labs +name: sent_logion_50k_wordpiece_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_logion_50k_wordpiece_pipeline` is a English model originally trained by cabrooks. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_logion_50k_wordpiece_pipeline_en_5.5.1_3.0_1731296537847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_logion_50k_wordpiece_pipeline_en_5.5.1_3.0_1731296537847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_logion_50k_wordpiece_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_logion_50k_wordpiece_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_logion_50k_wordpiece_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|464.7 MB| + +## References + +https://huggingface.co/cabrooks/LOGION-50k_wordpiece + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_mbert_resp_english_chinese_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_mbert_resp_english_chinese_en.md new file mode 100644 index 00000000000000..fde19de7c4545e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_mbert_resp_english_chinese_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_mbert_resp_english_chinese BertSentenceEmbeddings from nikitam +author: John Snow Labs +name: sent_mbert_resp_english_chinese +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbert_resp_english_chinese` is a English model originally trained by nikitam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mbert_resp_english_chinese_en_5.5.1_3.0_1731296372061.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbert_resp_english_chinese_en_5.5.1_3.0_1731296372061.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_mbert_resp_english_chinese","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_mbert_resp_english_chinese","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_mbert_resp_english_chinese| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|625.0 MB| + +## References + +https://huggingface.co/nikitam/mbert-resp-en-zh \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_mbert_resp_english_chinese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_mbert_resp_english_chinese_pipeline_en.md new file mode 100644 index 00000000000000..ac69c89b3dba18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_mbert_resp_english_chinese_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_mbert_resp_english_chinese_pipeline pipeline BertSentenceEmbeddings from nikitam +author: John Snow Labs +name: sent_mbert_resp_english_chinese_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_mbert_resp_english_chinese_pipeline` is a English model originally trained by nikitam. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_mbert_resp_english_chinese_pipeline_en_5.5.1_3.0_1731296403530.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_mbert_resp_english_chinese_pipeline_en_5.5.1_3.0_1731296403530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_mbert_resp_english_chinese_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_mbert_resp_english_chinese_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_mbert_resp_english_chinese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|625.6 MB| + +## References + +https://huggingface.co/nikitam/mbert-resp-en-zh + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_pak_legal_bert_small_uncased_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_pak_legal_bert_small_uncased_en.md new file mode 100644 index 00000000000000..0601d07658c3e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_pak_legal_bert_small_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_pak_legal_bert_small_uncased BertSentenceEmbeddings from AISystems +author: John Snow Labs +name: sent_pak_legal_bert_small_uncased +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pak_legal_bert_small_uncased` is a English model originally trained by AISystems. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pak_legal_bert_small_uncased_en_5.5.1_3.0_1731295493020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pak_legal_bert_small_uncased_en_5.5.1_3.0_1731295493020.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_pak_legal_bert_small_uncased","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_pak_legal_bert_small_uncased","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_pak_legal_bert_small_uncased| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|130.5 MB| + +## References + +https://huggingface.co/AISystems/PAK-LEGAL-BERT-small-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_pak_legal_bert_small_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_pak_legal_bert_small_uncased_pipeline_en.md new file mode 100644 index 00000000000000..0fb73d309e24bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_pak_legal_bert_small_uncased_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_pak_legal_bert_small_uncased_pipeline pipeline BertSentenceEmbeddings from AISystems +author: John Snow Labs +name: sent_pak_legal_bert_small_uncased_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_pak_legal_bert_small_uncased_pipeline` is a English model originally trained by AISystems. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_pak_legal_bert_small_uncased_pipeline_en_5.5.1_3.0_1731295500164.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_pak_legal_bert_small_uncased_pipeline_en_5.5.1_3.0_1731295500164.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_pak_legal_bert_small_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_pak_legal_bert_small_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_pak_legal_bert_small_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|131.1 MB| + +## References + +https://huggingface.co/AISystems/PAK-LEGAL-BERT-small-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_prunedbert_l12_h384_a6_finetuned_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_prunedbert_l12_h384_a6_finetuned_en.md new file mode 100644 index 00000000000000..786616bedc58fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_prunedbert_l12_h384_a6_finetuned_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_prunedbert_l12_h384_a6_finetuned BertSentenceEmbeddings from eli4s +author: John Snow Labs +name: sent_prunedbert_l12_h384_a6_finetuned +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_prunedbert_l12_h384_a6_finetuned` is a English model originally trained by eli4s. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_prunedbert_l12_h384_a6_finetuned_en_5.5.1_3.0_1731295988320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_prunedbert_l12_h384_a6_finetuned_en_5.5.1_3.0_1731295988320.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_prunedbert_l12_h384_a6_finetuned","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_prunedbert_l12_h384_a6_finetuned","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_prunedbert_l12_h384_a6_finetuned| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|176.4 MB| + +## References + +https://huggingface.co/eli4s/prunedBert-L12-h384-A6-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_prunedbert_l12_h384_a6_finetuned_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_prunedbert_l12_h384_a6_finetuned_pipeline_en.md new file mode 100644 index 00000000000000..809d46e5e4e899 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_prunedbert_l12_h384_a6_finetuned_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_prunedbert_l12_h384_a6_finetuned_pipeline pipeline BertSentenceEmbeddings from eli4s +author: John Snow Labs +name: sent_prunedbert_l12_h384_a6_finetuned_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_prunedbert_l12_h384_a6_finetuned_pipeline` is a English model originally trained by eli4s. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_prunedbert_l12_h384_a6_finetuned_pipeline_en_5.5.1_3.0_1731295997556.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_prunedbert_l12_h384_a6_finetuned_pipeline_en_5.5.1_3.0_1731295997556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_prunedbert_l12_h384_a6_finetuned_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_prunedbert_l12_h384_a6_finetuned_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_prunedbert_l12_h384_a6_finetuned_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|177.0 MB| + +## References + +https://huggingface.co/eli4s/prunedBert-L12-h384-A6-finetuned + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_structbert_large_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_structbert_large_en.md new file mode 100644 index 00000000000000..9d411c90eabd98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_structbert_large_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_structbert_large BertSentenceEmbeddings from bayartsogt +author: John Snow Labs +name: sent_structbert_large +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_structbert_large` is a English model originally trained by bayartsogt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_structbert_large_en_5.5.1_3.0_1731295741007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_structbert_large_en_5.5.1_3.0_1731295741007.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_structbert_large","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_structbert_large","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_structbert_large| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/bayartsogt/structbert-large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_structbert_large_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_structbert_large_pipeline_en.md new file mode 100644 index 00000000000000..f9545f81882ba4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_structbert_large_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_structbert_large_pipeline pipeline BertSentenceEmbeddings from bayartsogt +author: John Snow Labs +name: sent_structbert_large_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_structbert_large_pipeline` is a English model originally trained by bayartsogt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_structbert_large_pipeline_en_5.5.1_3.0_1731295805138.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_structbert_large_pipeline_en_5.5.1_3.0_1731295805138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_structbert_large_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_structbert_large_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_structbert_large_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/bayartsogt/structbert-large + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_mnli_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_mnli_en.md new file mode 100644 index 00000000000000..bd547fe49d2313 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_mnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_tiny_mlm_glue_mnli BertSentenceEmbeddings from muhtasham +author: John Snow Labs +name: sent_tiny_mlm_glue_mnli +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_mlm_glue_mnli` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_mnli_en_5.5.1_3.0_1731295597619.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_mnli_en_5.5.1_3.0_1731295597619.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_mlm_glue_mnli","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_mlm_glue_mnli","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_tiny_mlm_glue_mnli| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_mnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_mnli_pipeline_en.md new file mode 100644 index 00000000000000..01b0eedcdddeb1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_mnli_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_tiny_mlm_glue_mnli_pipeline pipeline BertSentenceEmbeddings from muhtasham +author: John Snow Labs +name: sent_tiny_mlm_glue_mnli_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_mlm_glue_mnli_pipeline` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_mnli_pipeline_en_5.5.1_3.0_1731295598891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_mnli_pipeline_en_5.5.1_3.0_1731295598891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_tiny_mlm_glue_mnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_tiny_mlm_glue_mnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_tiny_mlm_glue_mnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|17.2 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-mnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_qnli_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_qnli_en.md new file mode 100644 index 00000000000000..d3ccc3bf166267 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_qnli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_tiny_mlm_glue_qnli BertSentenceEmbeddings from muhtasham +author: John Snow Labs +name: sent_tiny_mlm_glue_qnli +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_mlm_glue_qnli` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_qnli_en_5.5.1_3.0_1731295911140.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_qnli_en_5.5.1_3.0_1731295911140.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_mlm_glue_qnli","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_mlm_glue_qnli","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_tiny_mlm_glue_qnli| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_qnli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_qnli_pipeline_en.md new file mode 100644 index 00000000000000..3fc10d23738b8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_glue_qnli_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_tiny_mlm_glue_qnli_pipeline pipeline BertSentenceEmbeddings from muhtasham +author: John Snow Labs +name: sent_tiny_mlm_glue_qnli_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_mlm_glue_qnli_pipeline` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_qnli_pipeline_en_5.5.1_3.0_1731295912316.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_glue_qnli_pipeline_en_5.5.1_3.0_1731295912316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_tiny_mlm_glue_qnli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_tiny_mlm_glue_qnli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_tiny_mlm_glue_qnli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|17.2 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-glue-qnli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_snli_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_snli_en.md new file mode 100644 index 00000000000000..59b38622e1e5e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_snli_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_tiny_mlm_snli BertSentenceEmbeddings from muhtasham +author: John Snow Labs +name: sent_tiny_mlm_snli +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_mlm_snli` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_snli_en_5.5.1_3.0_1731296115989.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_snli_en_5.5.1_3.0_1731296115989.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_mlm_snli","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_tiny_mlm_snli","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_tiny_mlm_snli| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-snli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_snli_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_snli_pipeline_en.md new file mode 100644 index 00000000000000..e1e8cbfe3b8e35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_tiny_mlm_snli_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_tiny_mlm_snli_pipeline pipeline BertSentenceEmbeddings from muhtasham +author: John Snow Labs +name: sent_tiny_mlm_snli_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tiny_mlm_snli_pipeline` is a English model originally trained by muhtasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_snli_pipeline_en_5.5.1_3.0_1731296117216.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tiny_mlm_snli_pipeline_en_5.5.1_3.0_1731296117216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_tiny_mlm_snli_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_tiny_mlm_snli_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_tiny_mlm_snli_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|17.2 MB| + +## References + +https://huggingface.co/muhtasham/tiny-mlm-snli + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_tinybert_javanese_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_tinybert_javanese_en.md new file mode 100644 index 00000000000000..1c92e04daee06f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_tinybert_javanese_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_tinybert_javanese BertSentenceEmbeddings from akahana +author: John Snow Labs +name: sent_tinybert_javanese +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tinybert_javanese` is a English model originally trained by akahana. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tinybert_javanese_en_5.5.1_3.0_1731296102820.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tinybert_javanese_en_5.5.1_3.0_1731296102820.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_tinybert_javanese","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_tinybert_javanese","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_tinybert_javanese| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|16.6 MB| + +## References + +https://huggingface.co/akahana/tinybert-javanese \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_tinybert_javanese_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_tinybert_javanese_pipeline_en.md new file mode 100644 index 00000000000000..0edbdfbd9bfaf9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_tinybert_javanese_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_tinybert_javanese_pipeline pipeline BertSentenceEmbeddings from akahana +author: John Snow Labs +name: sent_tinybert_javanese_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_tinybert_javanese_pipeline` is a English model originally trained by akahana. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_tinybert_javanese_pipeline_en_5.5.1_3.0_1731296104116.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_tinybert_javanese_pipeline_en_5.5.1_3.0_1731296104116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_tinybert_javanese_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_tinybert_javanese_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_tinybert_javanese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|17.2 MB| + +## References + +https://huggingface.co/akahana/tinybert-javanese + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_youtube_bert_10_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_youtube_bert_10_en.md new file mode 100644 index 00000000000000..ec8410874d4ce9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_youtube_bert_10_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sent_youtube_bert_10 BertSentenceEmbeddings from flboehm +author: John Snow Labs +name: sent_youtube_bert_10 +date: 2024-11-11 +tags: [en, open_source, onnx, sentence_embeddings, bert] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertSentenceEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_youtube_bert_10` is a English model originally trained by flboehm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_youtube_bert_10_en_5.5.1_3.0_1731296253290.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_youtube_bert_10_en_5.5.1_3.0_1731296253290.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") + +sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") \ + .setInputCols(["document"]) \ + .setOutputCol("sentence") + +embeddings = BertSentenceEmbeddings.pretrained("sent_youtube_bert_10","en") \ + .setInputCols(["sentence"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, sentenceDL, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val sentenceDL = SentenceDetectorDLModel.pretrained("sentence_detector_dl", "xx") + .setInputCols(Array("document")) + .setOutputCol("sentence") + +val embeddings = BertSentenceEmbeddings.pretrained("sent_youtube_bert_10","en") + .setInputCols(Array("sentence")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDL, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_youtube_bert_10| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|407.6 MB| + +## References + +https://huggingface.co/flboehm/youtube-bert_10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sent_youtube_bert_10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sent_youtube_bert_10_pipeline_en.md new file mode 100644 index 00000000000000..4d90e7434588fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sent_youtube_bert_10_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sent_youtube_bert_10_pipeline pipeline BertSentenceEmbeddings from flboehm +author: John Snow Labs +name: sent_youtube_bert_10_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertSentenceEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sent_youtube_bert_10_pipeline` is a English model originally trained by flboehm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sent_youtube_bert_10_pipeline_en_5.5.1_3.0_1731296274142.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sent_youtube_bert_10_pipeline_en_5.5.1_3.0_1731296274142.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sent_youtube_bert_10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sent_youtube_bert_10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sent_youtube_bert_10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/flboehm/youtube-bert_10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- SentenceDetectorDLModel +- BertSentenceEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sentence_similarity_finetuned_mpnet_adrta_en.md b/docs/_posts/ahmedlone127/2024-11-11-sentence_similarity_finetuned_mpnet_adrta_en.md new file mode 100644 index 00000000000000..3b878db8d41968 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sentence_similarity_finetuned_mpnet_adrta_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentence_similarity_finetuned_mpnet_adrta MPNetForSequenceClassification from aizenSosuke +author: John Snow Labs +name: sentence_similarity_finetuned_mpnet_adrta +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_similarity_finetuned_mpnet_adrta` is a English model originally trained by aizenSosuke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_similarity_finetuned_mpnet_adrta_en_5.5.1_3.0_1731301599861.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_similarity_finetuned_mpnet_adrta_en_5.5.1_3.0_1731301599861.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 = MPNetForSequenceClassification.pretrained("sentence_similarity_finetuned_mpnet_adrta","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("sentence_similarity_finetuned_mpnet_adrta", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_similarity_finetuned_mpnet_adrta| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/aizenSosuke/sentence-similarity-finetuned-mpnet-adrta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sentence_similarity_finetuned_mpnet_adrta_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sentence_similarity_finetuned_mpnet_adrta_pipeline_en.md new file mode 100644 index 00000000000000..f17efdad427243 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sentence_similarity_finetuned_mpnet_adrta_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentence_similarity_finetuned_mpnet_adrta_pipeline pipeline MPNetForSequenceClassification from aizenSosuke +author: John Snow Labs +name: sentence_similarity_finetuned_mpnet_adrta_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_similarity_finetuned_mpnet_adrta_pipeline` is a English model originally trained by aizenSosuke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_similarity_finetuned_mpnet_adrta_pipeline_en_5.5.1_3.0_1731301620394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_similarity_finetuned_mpnet_adrta_pipeline_en_5.5.1_3.0_1731301620394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentence_similarity_finetuned_mpnet_adrta_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentence_similarity_finetuned_mpnet_adrta_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_similarity_finetuned_mpnet_adrta_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/aizenSosuke/sentence-similarity-finetuned-mpnet-adrta + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sentence_transformers_all_mpnet_base_v2_en.md b/docs/_posts/ahmedlone127/2024-11-11-sentence_transformers_all_mpnet_base_v2_en.md new file mode 100644 index 00000000000000..655ee36269b0f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sentence_transformers_all_mpnet_base_v2_en.md @@ -0,0 +1,88 @@ +--- +layout: model +title: English sentence_transformers_all_mpnet_base_v2 MPNetEmbeddings from ai-human-lab +author: John Snow Labs +name: sentence_transformers_all_mpnet_base_v2 +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_all_mpnet_base_v2` is a English model originally trained by ai-human-lab. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_all_mpnet_base_v2_en_5.5.1_3.0_1731294868447.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_all_mpnet_base_v2_en_5.5.1_3.0_1731294868447.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") + +embeddings = MPNetEmbeddings.pretrained("sentence_transformers_all_mpnet_base_v2","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("sentence_transformers_all_mpnet_base_v2","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_transformers_all_mpnet_base_v2| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.9 MB| + +## References + +References + +https://huggingface.co/ai-human-lab/sentence-transformers_all-mpnet-base-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sentence_transformers_all_mpnet_base_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sentence_transformers_all_mpnet_base_v2_pipeline_en.md new file mode 100644 index 00000000000000..1014fb19af5de3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sentence_transformers_all_mpnet_base_v2_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English sentence_transformers_all_mpnet_base_v2_pipeline pipeline MPNetEmbeddings from ai-human-lab +author: John Snow Labs +name: sentence_transformers_all_mpnet_base_v2_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_transformers_all_mpnet_base_v2_pipeline` is a English model originally trained by ai-human-lab. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_transformers_all_mpnet_base_v2_pipeline_en_5.5.1_3.0_1731294890802.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_transformers_all_mpnet_base_v2_pipeline_en_5.5.1_3.0_1731294890802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +pipeline = PretrainedPipeline("sentence_transformers_all_mpnet_base_v2_pipeline", lang = "en") +annotations = pipeline.transform(df) +``` +```scala +val pipeline = new PretrainedPipeline("sentence_transformers_all_mpnet_base_v2_pipeline", lang = "en") +val annotations = pipeline.transform(df) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_transformers_all_mpnet_base_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.9 MB| + +## References + +References + +https://huggingface.co/ai-human-lab/sentence-transformers_all-mpnet-base-v2 + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_ftmodel_on_chemical_dataset_en.md b/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_ftmodel_on_chemical_dataset_en.md new file mode 100644 index 00000000000000..45619df65fac6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_ftmodel_on_chemical_dataset_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English sentencetransformer_ftmodel_on_chemical_dataset MPNetEmbeddings from Saideepthi55 +author: John Snow Labs +name: sentencetransformer_ftmodel_on_chemical_dataset +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentencetransformer_ftmodel_on_chemical_dataset` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentencetransformer_ftmodel_on_chemical_dataset_en_5.5.1_3.0_1731295029219.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentencetransformer_ftmodel_on_chemical_dataset_en_5.5.1_3.0_1731295029219.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") + +embeddings = MPNetEmbeddings.pretrained("sentencetransformer_ftmodel_on_chemical_dataset","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("sentencetransformer_ftmodel_on_chemical_dataset","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentencetransformer_ftmodel_on_chemical_dataset| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|402.5 MB| + +## References + +https://huggingface.co/Saideepthi55/sentencetransformer_ftmodel_on_chemical_dataset \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_ftmodel_on_chemical_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_ftmodel_on_chemical_dataset_pipeline_en.md new file mode 100644 index 00000000000000..cd8788d4ba267c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_ftmodel_on_chemical_dataset_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English sentencetransformer_ftmodel_on_chemical_dataset_pipeline pipeline MPNetEmbeddings from Saideepthi55 +author: John Snow Labs +name: sentencetransformer_ftmodel_on_chemical_dataset_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentencetransformer_ftmodel_on_chemical_dataset_pipeline` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentencetransformer_ftmodel_on_chemical_dataset_pipeline_en_5.5.1_3.0_1731295052812.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentencetransformer_ftmodel_on_chemical_dataset_pipeline_en_5.5.1_3.0_1731295052812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentencetransformer_ftmodel_on_chemical_dataset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentencetransformer_ftmodel_on_chemical_dataset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentencetransformer_ftmodel_on_chemical_dataset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|402.5 MB| + +## References + +https://huggingface.co/Saideepthi55/sentencetransformer_ftmodel_on_chemical_dataset + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_mpnet_base_on_chemical_dataset_en.md b/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_mpnet_base_on_chemical_dataset_en.md new file mode 100644 index 00000000000000..d5045ad86dd36b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_mpnet_base_on_chemical_dataset_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sentencetransformer_mpnet_base_on_chemical_dataset MPNetForSequenceClassification from Saideepthi55 +author: John Snow Labs +name: sentencetransformer_mpnet_base_on_chemical_dataset +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentencetransformer_mpnet_base_on_chemical_dataset` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentencetransformer_mpnet_base_on_chemical_dataset_en_5.5.1_3.0_1731301268354.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentencetransformer_mpnet_base_on_chemical_dataset_en_5.5.1_3.0_1731301268354.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 = MPNetForSequenceClassification.pretrained("sentencetransformer_mpnet_base_on_chemical_dataset","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("sentencetransformer_mpnet_base_on_chemical_dataset", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentencetransformer_mpnet_base_on_chemical_dataset| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|263.5 MB| + +## References + +https://huggingface.co/Saideepthi55/sentencetransformer_mpnet_base_on_chemical_dataset \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_mpnet_base_on_chemical_dataset_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_mpnet_base_on_chemical_dataset_pipeline_en.md new file mode 100644 index 00000000000000..6b0b2bd45c68ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sentencetransformer_mpnet_base_on_chemical_dataset_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sentencetransformer_mpnet_base_on_chemical_dataset_pipeline pipeline MPNetForSequenceClassification from Saideepthi55 +author: John Snow Labs +name: sentencetransformer_mpnet_base_on_chemical_dataset_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentencetransformer_mpnet_base_on_chemical_dataset_pipeline` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentencetransformer_mpnet_base_on_chemical_dataset_pipeline_en_5.5.1_3.0_1731301346750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentencetransformer_mpnet_base_on_chemical_dataset_pipeline_en_5.5.1_3.0_1731301346750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sentencetransformer_mpnet_base_on_chemical_dataset_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sentencetransformer_mpnet_base_on_chemical_dataset_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentencetransformer_mpnet_base_on_chemical_dataset_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|263.5 MB| + +## References + +https://huggingface.co/Saideepthi55/sentencetransformer_mpnet_base_on_chemical_dataset + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-setfit_model_ireland_4labels_unbalanced_data_en.md b/docs/_posts/ahmedlone127/2024-11-11-setfit_model_ireland_4labels_unbalanced_data_en.md new file mode 100644 index 00000000000000..f6651ad90e1108 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-setfit_model_ireland_4labels_unbalanced_data_en.md @@ -0,0 +1,86 @@ +--- +layout: model +title: English setfit_model_ireland_4labels_unbalanced_data MPNetEmbeddings from mitra-mir +author: John Snow Labs +name: setfit_model_ireland_4labels_unbalanced_data +date: 2024-11-11 +tags: [en, open_source, onnx, embeddings, mpnet] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_ireland_4labels_unbalanced_data` is a English model originally trained by mitra-mir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_4labels_unbalanced_data_en_5.5.1_3.0_1731294943741.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_4labels_unbalanced_data_en_5.5.1_3.0_1731294943741.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") + +embeddings = MPNetEmbeddings.pretrained("setfit_model_ireland_4labels_unbalanced_data","en") \ + .setInputCols(["document"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([documentAssembler, embeddings]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val embeddings = MPNetEmbeddings.pretrained("setfit_model_ireland_4labels_unbalanced_data","en") + .setInputCols(Array("document")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, embeddings)) +val data = Seq("I love spark-nlp").toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_model_ireland_4labels_unbalanced_data| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document]| +|Output Labels:|[mpnet]| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/mitra-mir/setfit-model-Ireland_4labels_unbalanced_data \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-setfit_model_ireland_4labels_unbalanced_data_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-setfit_model_ireland_4labels_unbalanced_data_pipeline_en.md new file mode 100644 index 00000000000000..562b9e139b615d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-setfit_model_ireland_4labels_unbalanced_data_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English setfit_model_ireland_4labels_unbalanced_data_pipeline pipeline MPNetEmbeddings from mitra-mir +author: John Snow Labs +name: setfit_model_ireland_4labels_unbalanced_data_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetEmbeddings, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`setfit_model_ireland_4labels_unbalanced_data_pipeline` is a English model originally trained by mitra-mir. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_4labels_unbalanced_data_pipeline_en_5.5.1_3.0_1731294965484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/setfit_model_ireland_4labels_unbalanced_data_pipeline_en_5.5.1_3.0_1731294965484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("setfit_model_ireland_4labels_unbalanced_data_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("setfit_model_ireland_4labels_unbalanced_data_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|setfit_model_ireland_4labels_unbalanced_data_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.8 MB| + +## References + +https://huggingface.co/mitra-mir/setfit-model-Ireland_4labels_unbalanced_data + +## Included Models + +- DocumentAssembler +- MPNetEmbeddings \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-software_ner_prod_en.md b/docs/_posts/ahmedlone127/2024-11-11-software_ner_prod_en.md new file mode 100644 index 00000000000000..304fef613f4f5b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-software_ner_prod_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English software_ner_prod BertForTokenClassification from hadiaskari98 +author: John Snow Labs +name: software_ner_prod +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`software_ner_prod` is a English model originally trained by hadiaskari98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/software_ner_prod_en_5.5.1_3.0_1731298584900.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/software_ner_prod_en_5.5.1_3.0_1731298584900.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') + +tokenClassifier = BertForTokenClassification.pretrained("software_ner_prod","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("software_ner_prod", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|software_ner_prod| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/hadiaskari98/Software_NER_prod \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-software_ner_prod_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-software_ner_prod_pipeline_en.md new file mode 100644 index 00000000000000..914e298fd6beab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-software_ner_prod_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English software_ner_prod_pipeline pipeline BertForTokenClassification from hadiaskari98 +author: John Snow Labs +name: software_ner_prod_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`software_ner_prod_pipeline` is a English model originally trained by hadiaskari98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/software_ner_prod_pipeline_en_5.5.1_3.0_1731298649868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/software_ner_prod_pipeline_en_5.5.1_3.0_1731298649868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("software_ner_prod_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("software_ner_prod_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|software_ner_prod_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/hadiaskari98/Software_NER_prod + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base10_en.md b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base10_en.md new file mode 100644 index 00000000000000..46612537643cc3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base10_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English southern_sotho_mpnet_base10 MPNetForSequenceClassification from Saideepthi55 +author: John Snow Labs +name: southern_sotho_mpnet_base10 +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_mpnet_base10` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base10_en_5.5.1_3.0_1731301271163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base10_en_5.5.1_3.0_1731301271163.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 = MPNetForSequenceClassification.pretrained("southern_sotho_mpnet_base10","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("southern_sotho_mpnet_base10", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|southern_sotho_mpnet_base10| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/Saideepthi55/st_mpnet_base10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base10_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base10_pipeline_en.md new file mode 100644 index 00000000000000..cbf94edb9db76f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base10_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English southern_sotho_mpnet_base10_pipeline pipeline MPNetForSequenceClassification from Saideepthi55 +author: John Snow Labs +name: southern_sotho_mpnet_base10_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_mpnet_base10_pipeline` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base10_pipeline_en_5.5.1_3.0_1731301299330.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base10_pipeline_en_5.5.1_3.0_1731301299330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("southern_sotho_mpnet_base10_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("southern_sotho_mpnet_base10_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|southern_sotho_mpnet_base10_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/Saideepthi55/st_mpnet_base10 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base20_en.md b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base20_en.md new file mode 100644 index 00000000000000..34e20462124c15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base20_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English southern_sotho_mpnet_base20 MPNetForSequenceClassification from Saideepthi55 +author: John Snow Labs +name: southern_sotho_mpnet_base20 +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_mpnet_base20` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base20_en_5.5.1_3.0_1731301543132.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base20_en_5.5.1_3.0_1731301543132.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 = MPNetForSequenceClassification.pretrained("southern_sotho_mpnet_base20","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("southern_sotho_mpnet_base20", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|southern_sotho_mpnet_base20| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/Saideepthi55/st_mpnet_base20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base20_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base20_pipeline_en.md new file mode 100644 index 00000000000000..6243a692d93e7e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base20_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English southern_sotho_mpnet_base20_pipeline pipeline MPNetForSequenceClassification from Saideepthi55 +author: John Snow Labs +name: southern_sotho_mpnet_base20_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_mpnet_base20_pipeline` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base20_pipeline_en_5.5.1_3.0_1731301564358.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base20_pipeline_en_5.5.1_3.0_1731301564358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("southern_sotho_mpnet_base20_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("southern_sotho_mpnet_base20_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|southern_sotho_mpnet_base20_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/Saideepthi55/st_mpnet_base20 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base_normal_en.md b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base_normal_en.md new file mode 100644 index 00000000000000..fa19b9f0f12d22 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base_normal_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English southern_sotho_mpnet_base_normal MPNetForSequenceClassification from Saideepthi55 +author: John Snow Labs +name: southern_sotho_mpnet_base_normal +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_mpnet_base_normal` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base_normal_en_5.5.1_3.0_1731301340152.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base_normal_en_5.5.1_3.0_1731301340152.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 = MPNetForSequenceClassification.pretrained("southern_sotho_mpnet_base_normal","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("southern_sotho_mpnet_base_normal", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|southern_sotho_mpnet_base_normal| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/Saideepthi55/st_mpnet_base_normal \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base_normal_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base_normal_pipeline_en.md new file mode 100644 index 00000000000000..ccd69f639b6519 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-southern_sotho_mpnet_base_normal_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English southern_sotho_mpnet_base_normal_pipeline pipeline MPNetForSequenceClassification from Saideepthi55 +author: John Snow Labs +name: southern_sotho_mpnet_base_normal_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`southern_sotho_mpnet_base_normal_pipeline` is a English model originally trained by Saideepthi55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base_normal_pipeline_en_5.5.1_3.0_1731301362624.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/southern_sotho_mpnet_base_normal_pipeline_en_5.5.1_3.0_1731301362624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("southern_sotho_mpnet_base_normal_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("southern_sotho_mpnet_base_normal_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|southern_sotho_mpnet_base_normal_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/Saideepthi55/st_mpnet_base_normal + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-spanish_medical_ner_es.md b/docs/_posts/ahmedlone127/2024-11-11-spanish_medical_ner_es.md new file mode 100644 index 00000000000000..32940e8b7f748a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-spanish_medical_ner_es.md @@ -0,0 +1,94 @@ +--- +layout: model +title: Castilian, Spanish spanish_medical_ner BertForTokenClassification from HUMADEX +author: John Snow Labs +name: spanish_medical_ner +date: 2024-11-11 +tags: [es, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_medical_ner` is a Castilian, Spanish model originally trained by HUMADEX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_medical_ner_es_5.5.1_3.0_1731299312525.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_medical_ner_es_5.5.1_3.0_1731299312525.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') + +tokenClassifier = BertForTokenClassification.pretrained("spanish_medical_ner","es") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("spanish_medical_ner", "es") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_medical_ner| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|403.7 MB| + +## References + +https://huggingface.co/HUMADEX/spanish_medical_ner \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-spanish_medical_ner_pipeline_es.md b/docs/_posts/ahmedlone127/2024-11-11-spanish_medical_ner_pipeline_es.md new file mode 100644 index 00000000000000..9b0dd5371d3052 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-spanish_medical_ner_pipeline_es.md @@ -0,0 +1,70 @@ +--- +layout: model +title: Castilian, Spanish spanish_medical_ner_pipeline pipeline BertForTokenClassification from HUMADEX +author: John Snow Labs +name: spanish_medical_ner_pipeline +date: 2024-11-11 +tags: [es, open_source, pipeline, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanish_medical_ner_pipeline` is a Castilian, Spanish model originally trained by HUMADEX. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanish_medical_ner_pipeline_es_5.5.1_3.0_1731299333046.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanish_medical_ner_pipeline_es_5.5.1_3.0_1731299333046.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("spanish_medical_ner_pipeline", lang = "es") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("spanish_medical_ner_pipeline", lang = "es") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanish_medical_ner_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|403.7 MB| + +## References + +https://huggingface.co/HUMADEX/spanish_medical_ner + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sst2_benign_bert_uncased_en.md b/docs/_posts/ahmedlone127/2024-11-11-sst2_benign_bert_uncased_en.md new file mode 100644 index 00000000000000..8a15ca8acffe06 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sst2_benign_bert_uncased_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sst2_benign_bert_uncased BertForSequenceClassification from dilarayavuz +author: John Snow Labs +name: sst2_benign_bert_uncased +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sst2_benign_bert_uncased` is a English model originally trained by dilarayavuz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sst2_benign_bert_uncased_en_5.5.1_3.0_1731309631235.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sst2_benign_bert_uncased_en_5.5.1_3.0_1731309631235.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("sst2_benign_bert_uncased","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sst2_benign_bert_uncased", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sst2_benign_bert_uncased| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/dilarayavuz/sst2-benign-bert-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sst2_benign_bert_uncased_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sst2_benign_bert_uncased_pipeline_en.md new file mode 100644 index 00000000000000..622065dfccca22 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sst2_benign_bert_uncased_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sst2_benign_bert_uncased_pipeline pipeline BertForSequenceClassification from dilarayavuz +author: John Snow Labs +name: sst2_benign_bert_uncased_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sst2_benign_bert_uncased_pipeline` is a English model originally trained by dilarayavuz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sst2_benign_bert_uncased_pipeline_en_5.5.1_3.0_1731309652958.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sst2_benign_bert_uncased_pipeline_en_5.5.1_3.0_1731309652958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sst2_benign_bert_uncased_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sst2_benign_bert_uncased_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sst2_benign_bert_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/dilarayavuz/sst2-benign-bert-uncased + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sysformver1_en.md b/docs/_posts/ahmedlone127/2024-11-11-sysformver1_en.md new file mode 100644 index 00000000000000..6df9fcc3dcdeab --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sysformver1_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English sysformver1 BertForTokenClassification from blckwdw61 +author: John Snow Labs +name: sysformver1 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sysformver1` is a English model originally trained by blckwdw61. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sysformver1_en_5.5.1_3.0_1731291183659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sysformver1_en_5.5.1_3.0_1731291183659.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') + +tokenClassifier = BertForTokenClassification.pretrained("sysformver1","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("sysformver1", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sysformver1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/blckwdw61/sysformver1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-sysformver1_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-sysformver1_pipeline_en.md new file mode 100644 index 00000000000000..1b88c0aed34dec --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-sysformver1_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English sysformver1_pipeline pipeline BertForTokenClassification from blckwdw61 +author: John Snow Labs +name: sysformver1_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sysformver1_pipeline` is a English model originally trained by blckwdw61. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sysformver1_pipeline_en_5.5.1_3.0_1731291209752.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sysformver1_pipeline_en_5.5.1_3.0_1731291209752.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("sysformver1_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("sysformver1_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sysformver1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.7 MB| + +## References + +https://huggingface.co/blckwdw61/sysformver1 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytest_en.md b/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytest_en.md new file mode 100644 index 00000000000000..0fe26267d56c1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytest_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English testthesissmallfiftytest BertForTokenClassification from Nonzerophilip +author: John Snow Labs +name: testthesissmallfiftytest +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testthesissmallfiftytest` is a English model originally trained by Nonzerophilip. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testthesissmallfiftytest_en_5.5.1_3.0_1731285202383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testthesissmallfiftytest_en_5.5.1_3.0_1731285202383.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') + +tokenClassifier = BertForTokenClassification.pretrained("testthesissmallfiftytest","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("testthesissmallfiftytest", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testthesissmallfiftytest| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|465.3 MB| + +## References + +https://huggingface.co/Nonzerophilip/testThesisSmallfiftyTEST \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytest_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytest_pipeline_en.md new file mode 100644 index 00000000000000..2911e0f4f34e5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytest_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English testthesissmallfiftytest_pipeline pipeline BertForTokenClassification from Nonzerophilip +author: John Snow Labs +name: testthesissmallfiftytest_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testthesissmallfiftytest_pipeline` is a English model originally trained by Nonzerophilip. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testthesissmallfiftytest_pipeline_en_5.5.1_3.0_1731285227026.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testthesissmallfiftytest_pipeline_en_5.5.1_3.0_1731285227026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("testthesissmallfiftytest_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("testthesissmallfiftytest_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testthesissmallfiftytest_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.3 MB| + +## References + +https://huggingface.co/Nonzerophilip/testThesisSmallfiftyTEST + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytestaugfivegpt_en.md b/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytestaugfivegpt_en.md new file mode 100644 index 00000000000000..3ab88e365824f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytestaugfivegpt_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English testthesissmallfiftytestaugfivegpt BertForTokenClassification from Nonzerophilip +author: John Snow Labs +name: testthesissmallfiftytestaugfivegpt +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testthesissmallfiftytestaugfivegpt` is a English model originally trained by Nonzerophilip. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testthesissmallfiftytestaugfivegpt_en_5.5.1_3.0_1731285482289.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testthesissmallfiftytestaugfivegpt_en_5.5.1_3.0_1731285482289.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') + +tokenClassifier = BertForTokenClassification.pretrained("testthesissmallfiftytestaugfivegpt","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("testthesissmallfiftytestaugfivegpt", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testthesissmallfiftytestaugfivegpt| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|465.3 MB| + +## References + +https://huggingface.co/Nonzerophilip/testThesisSmallfiftyTESTAugfiveGPT \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytestaugfivegpt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytestaugfivegpt_pipeline_en.md new file mode 100644 index 00000000000000..dcdddde4fb8a3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-testthesissmallfiftytestaugfivegpt_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English testthesissmallfiftytestaugfivegpt_pipeline pipeline BertForTokenClassification from Nonzerophilip +author: John Snow Labs +name: testthesissmallfiftytestaugfivegpt_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`testthesissmallfiftytestaugfivegpt_pipeline` is a English model originally trained by Nonzerophilip. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/testthesissmallfiftytestaugfivegpt_pipeline_en_5.5.1_3.0_1731285506982.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/testthesissmallfiftytestaugfivegpt_pipeline_en_5.5.1_3.0_1731285506982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("testthesissmallfiftytestaugfivegpt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("testthesissmallfiftytestaugfivegpt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|testthesissmallfiftytestaugfivegpt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.3 MB| + +## References + +https://huggingface.co/Nonzerophilip/testThesisSmallfiftyTESTAugfiveGPT + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-tinybert_keyword_en.md b/docs/_posts/ahmedlone127/2024-11-11-tinybert_keyword_en.md new file mode 100644 index 00000000000000..9b8182548bfd73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-tinybert_keyword_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English tinybert_keyword BertForTokenClassification from nirusanan +author: John Snow Labs +name: tinybert_keyword +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinybert_keyword` is a English model originally trained by nirusanan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinybert_keyword_en_5.5.1_3.0_1731290570020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinybert_keyword_en_5.5.1_3.0_1731290570020.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') + +tokenClassifier = BertForTokenClassification.pretrained("tinybert_keyword","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("tinybert_keyword", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinybert_keyword| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|53.9 MB| + +## References + +https://huggingface.co/nirusanan/tinyBert-keyword \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-tinybert_keyword_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-tinybert_keyword_pipeline_en.md new file mode 100644 index 00000000000000..6e24c0b8d71454 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-tinybert_keyword_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English tinybert_keyword_pipeline pipeline BertForTokenClassification from nirusanan +author: John Snow Labs +name: tinybert_keyword_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinybert_keyword_pipeline` is a English model originally trained by nirusanan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinybert_keyword_pipeline_en_5.5.1_3.0_1731290572847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinybert_keyword_pipeline_en_5.5.1_3.0_1731290572847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("tinybert_keyword_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("tinybert_keyword_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinybert_keyword_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|53.9 MB| + +## References + +https://huggingface.co/nirusanan/tinyBert-keyword + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-token_classification_wnut_en.md b/docs/_posts/ahmedlone127/2024-11-11-token_classification_wnut_en.md new file mode 100644 index 00000000000000..cc75f3d6017e56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-token_classification_wnut_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English token_classification_wnut BertForTokenClassification from StatsGary +author: John Snow Labs +name: token_classification_wnut +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`token_classification_wnut` is a English model originally trained by StatsGary. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/token_classification_wnut_en_5.5.1_3.0_1731290160734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/token_classification_wnut_en_5.5.1_3.0_1731290160734.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') + +tokenClassifier = BertForTokenClassification.pretrained("token_classification_wnut","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("token_classification_wnut", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|token_classification_wnut| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StatsGary/token_classification_wnut \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-token_classification_wnut_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-token_classification_wnut_pipeline_en.md new file mode 100644 index 00000000000000..420e8725a1dc31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-token_classification_wnut_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English token_classification_wnut_pipeline pipeline BertForTokenClassification from StatsGary +author: John Snow Labs +name: token_classification_wnut_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`token_classification_wnut_pipeline` is a English model originally trained by StatsGary. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/token_classification_wnut_pipeline_en_5.5.1_3.0_1731290224907.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/token_classification_wnut_pipeline_en_5.5.1_3.0_1731290224907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("token_classification_wnut_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("token_classification_wnut_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|token_classification_wnut_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/StatsGary/token_classification_wnut + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-unified_skill_ner_echo_en.md b/docs/_posts/ahmedlone127/2024-11-11-unified_skill_ner_echo_en.md new file mode 100644 index 00000000000000..8a5a646aabe269 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-unified_skill_ner_echo_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English unified_skill_ner_echo BertForTokenClassification from ledigajobb +author: John Snow Labs +name: unified_skill_ner_echo +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unified_skill_ner_echo` is a English model originally trained by ledigajobb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unified_skill_ner_echo_en_5.5.1_3.0_1731298457277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unified_skill_ner_echo_en_5.5.1_3.0_1731298457277.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') + +tokenClassifier = BertForTokenClassification.pretrained("unified_skill_ner_echo","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("unified_skill_ner_echo", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unified_skill_ner_echo| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|465.5 MB| + +## References + +https://huggingface.co/ledigajobb/unified_skill_ner_echo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-unified_skill_ner_echo_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-unified_skill_ner_echo_pipeline_en.md new file mode 100644 index 00000000000000..ca82b108bc2710 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-unified_skill_ner_echo_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English unified_skill_ner_echo_pipeline pipeline BertForTokenClassification from ledigajobb +author: John Snow Labs +name: unified_skill_ner_echo_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unified_skill_ner_echo_pipeline` is a English model originally trained by ledigajobb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unified_skill_ner_echo_pipeline_en_5.5.1_3.0_1731298481375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unified_skill_ner_echo_pipeline_en_5.5.1_3.0_1731298481375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("unified_skill_ner_echo_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("unified_skill_ner_echo_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unified_skill_ner_echo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|465.5 MB| + +## References + +https://huggingface.co/ledigajobb/unified_skill_ner_echo + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-unitku_hubert_japanese_asr_ja.md b/docs/_posts/ahmedlone127/2024-11-11-unitku_hubert_japanese_asr_ja.md new file mode 100644 index 00000000000000..417b3e2e316059 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-unitku_hubert_japanese_asr_ja.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Japanese unitku_hubert_japanese_asr HubertForCTC from TKU410410103 +author: John Snow Labs +name: unitku_hubert_japanese_asr +date: 2024-11-11 +tags: [ja, open_source, onnx, asr, hubert] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: HubertForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unitku_hubert_japanese_asr` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unitku_hubert_japanese_asr_ja_5.5.1_3.0_1731284872906.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unitku_hubert_japanese_asr_ja_5.5.1_3.0_1731284872906.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 = HubertForCTC.pretrained("unitku_hubert_japanese_asr","ja") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = HubertForCTC.pretrained("unitku_hubert_japanese_asr", "ja") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unitku_hubert_japanese_asr| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ja| +|Size:|708.5 MB| + +## References + +https://huggingface.co/TKU410410103/uniTKU-hubert-japanese-asr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-unitku_hubert_japanese_asr_pipeline_ja.md b/docs/_posts/ahmedlone127/2024-11-11-unitku_hubert_japanese_asr_pipeline_ja.md new file mode 100644 index 00000000000000..dc49a94087aae7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-unitku_hubert_japanese_asr_pipeline_ja.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Japanese unitku_hubert_japanese_asr_pipeline pipeline HubertForCTC from TKU410410103 +author: John Snow Labs +name: unitku_hubert_japanese_asr_pipeline +date: 2024-11-11 +tags: [ja, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained HubertForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`unitku_hubert_japanese_asr_pipeline` is a Japanese model originally trained by TKU410410103. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/unitku_hubert_japanese_asr_pipeline_ja_5.5.1_3.0_1731284908856.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/unitku_hubert_japanese_asr_pipeline_ja_5.5.1_3.0_1731284908856.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("unitku_hubert_japanese_asr_pipeline", lang = "ja") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("unitku_hubert_japanese_asr_pipeline", lang = "ja") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|unitku_hubert_japanese_asr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|708.5 MB| + +## References + +https://huggingface.co/TKU410410103/uniTKU-hubert-japanese-asr + +## Included Models + +- AudioAssembler +- HubertForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-welt_biobert_ncbi_en.md b/docs/_posts/ahmedlone127/2024-11-11-welt_biobert_ncbi_en.md new file mode 100644 index 00000000000000..6b45f66b9da41b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-welt_biobert_ncbi_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English welt_biobert_ncbi BertForTokenClassification from ghadeermobasher +author: John Snow Labs +name: welt_biobert_ncbi +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, bert, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`welt_biobert_ncbi` is a English model originally trained by ghadeermobasher. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/welt_biobert_ncbi_en_5.5.1_3.0_1731285897383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/welt_biobert_ncbi_en_5.5.1_3.0_1731285897383.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') + +tokenClassifier = BertForTokenClassification.pretrained("welt_biobert_ncbi","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = BertForTokenClassification.pretrained("welt_biobert_ncbi", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|welt_biobert_ncbi| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/ghadeermobasher/WELT-BioBERT-NCBI \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-welt_biobert_ncbi_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-welt_biobert_ncbi_pipeline_en.md new file mode 100644 index 00000000000000..7a02552d647c15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-welt_biobert_ncbi_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English welt_biobert_ncbi_pipeline pipeline BertForTokenClassification from ghadeermobasher +author: John Snow Labs +name: welt_biobert_ncbi_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`welt_biobert_ncbi_pipeline` is a English model originally trained by ghadeermobasher. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/welt_biobert_ncbi_pipeline_en_5.5.1_3.0_1731285921198.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/welt_biobert_ncbi_pipeline_en_5.5.1_3.0_1731285921198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("welt_biobert_ncbi_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("welt_biobert_ncbi_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|welt_biobert_ncbi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|403.1 MB| + +## References + +https://huggingface.co/ghadeermobasher/WELT-BioBERT-NCBI + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_base_common_voice_arabic11_0_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_base_common_voice_arabic11_0_en.md new file mode 100644 index 00000000000000..d72472c08a233d --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_base_common_voice_arabic11_0_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_base_common_voice_arabic11_0 WhisperForCTC from Abdo96 +author: John Snow Labs +name: whisper_base_common_voice_arabic11_0 +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_base_common_voice_arabic11_0` is a English model originally trained by Abdo96. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_common_voice_arabic11_0_en_5.5.1_3.0_1731304414617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_common_voice_arabic11_0_en_5.5.1_3.0_1731304414617.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("whisper_base_common_voice_arabic11_0","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_base_common_voice_arabic11_0", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_common_voice_arabic11_0| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|642.3 MB| + +## References + +https://huggingface.co/Abdo96/whisper-base-common-voice-Arabic11.0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_base_common_voice_arabic11_0_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_base_common_voice_arabic11_0_pipeline_en.md new file mode 100644 index 00000000000000..e6395ff989f713 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_base_common_voice_arabic11_0_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_base_common_voice_arabic11_0_pipeline pipeline WhisperForCTC from Abdo96 +author: John Snow Labs +name: whisper_base_common_voice_arabic11_0_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_base_common_voice_arabic11_0_pipeline` is a English model originally trained by Abdo96. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_common_voice_arabic11_0_pipeline_en_5.5.1_3.0_1731304449172.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_common_voice_arabic11_0_pipeline_en_5.5.1_3.0_1731304449172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_base_common_voice_arabic11_0_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_base_common_voice_arabic11_0_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_common_voice_arabic11_0_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|642.4 MB| + +## References + +https://huggingface.co/Abdo96/whisper-base-common-voice-Arabic11.0 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_base_hungarian_v1_hu.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_base_hungarian_v1_hu.md new file mode 100644 index 00000000000000..e24bde593dcfd0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_base_hungarian_v1_hu.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Hungarian whisper_base_hungarian_v1 WhisperForCTC from sarpba +author: John Snow Labs +name: whisper_base_hungarian_v1 +date: 2024-11-11 +tags: [hu, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: hu +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_base_hungarian_v1` is a Hungarian model originally trained by sarpba. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_hungarian_v1_hu_5.5.1_3.0_1731304667467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_hungarian_v1_hu_5.5.1_3.0_1731304667467.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("whisper_base_hungarian_v1","hu") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_base_hungarian_v1", "hu") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_hungarian_v1| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|hu| +|Size:|643.4 MB| + +## References + +https://huggingface.co/sarpba/whisper-base-hungarian_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_base_hungarian_v1_pipeline_hu.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_base_hungarian_v1_pipeline_hu.md new file mode 100644 index 00000000000000..983b44d5fb09ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_base_hungarian_v1_pipeline_hu.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Hungarian whisper_base_hungarian_v1_pipeline pipeline WhisperForCTC from sarpba +author: John Snow Labs +name: whisper_base_hungarian_v1_pipeline +date: 2024-11-11 +tags: [hu, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: hu +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_base_hungarian_v1_pipeline` is a Hungarian model originally trained by sarpba. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_base_hungarian_v1_pipeline_hu_5.5.1_3.0_1731304705195.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_base_hungarian_v1_pipeline_hu_5.5.1_3.0_1731304705195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_base_hungarian_v1_pipeline", lang = "hu") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_base_hungarian_v1_pipeline", lang = "hu") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_base_hungarian_v1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|hu| +|Size:|643.4 MB| + +## References + +https://huggingface.co/sarpba/whisper-base-hungarian_v1 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_finetuned_atcosim_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_finetuned_atcosim_en.md new file mode 100644 index 00000000000000..d564ea07b24a65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_finetuned_atcosim_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_finetuned_atcosim WhisperForCTC from bhattasp +author: John Snow Labs +name: whisper_finetuned_atcosim +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_finetuned_atcosim` is a English model originally trained by bhattasp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_finetuned_atcosim_en_5.5.1_3.0_1731304932861.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_finetuned_atcosim_en_5.5.1_3.0_1731304932861.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("whisper_finetuned_atcosim","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_finetuned_atcosim", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_finetuned_atcosim| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|389.9 MB| + +## References + +https://huggingface.co/bhattasp/whisper-finetuned-atcosim \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_finetuned_atcosim_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_finetuned_atcosim_pipeline_en.md new file mode 100644 index 00000000000000..4ea36338ea9182 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_finetuned_atcosim_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_finetuned_atcosim_pipeline pipeline WhisperForCTC from bhattasp +author: John Snow Labs +name: whisper_finetuned_atcosim_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_finetuned_atcosim_pipeline` is a English model originally trained by bhattasp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_finetuned_atcosim_pipeline_en_5.5.1_3.0_1731304954819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_finetuned_atcosim_pipeline_en_5.5.1_3.0_1731304954819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_finetuned_atcosim_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_finetuned_atcosim_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_finetuned_atcosim_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|389.9 MB| + +## References + +https://huggingface.co/bhattasp/whisper-finetuned-atcosim + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_latvian_ver2_lv.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_latvian_ver2_lv.md new file mode 100644 index 00000000000000..4e07ccde16313e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_latvian_ver2_lv.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Latvian whisper_medium_latvian_ver2 WhisperForCTC from FelixK7 +author: John Snow Labs +name: whisper_medium_latvian_ver2 +date: 2024-11-11 +tags: [lv, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: lv +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_medium_latvian_ver2` is a Latvian model originally trained by FelixK7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_medium_latvian_ver2_lv_5.5.1_3.0_1731305211676.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_medium_latvian_ver2_lv_5.5.1_3.0_1731305211676.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("whisper_medium_latvian_ver2","lv") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_medium_latvian_ver2", "lv") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_medium_latvian_ver2| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|lv| +|Size:|4.8 GB| + +## References + +https://huggingface.co/FelixK7/whisper-medium-lv-ver2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_latvian_ver2_pipeline_lv.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_latvian_ver2_pipeline_lv.md new file mode 100644 index 00000000000000..841f62d981e9b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_latvian_ver2_pipeline_lv.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Latvian whisper_medium_latvian_ver2_pipeline pipeline WhisperForCTC from FelixK7 +author: John Snow Labs +name: whisper_medium_latvian_ver2_pipeline +date: 2024-11-11 +tags: [lv, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: lv +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_medium_latvian_ver2_pipeline` is a Latvian model originally trained by FelixK7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_medium_latvian_ver2_pipeline_lv_5.5.1_3.0_1731305454634.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_medium_latvian_ver2_pipeline_lv_5.5.1_3.0_1731305454634.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_medium_latvian_ver2_pipeline", lang = "lv") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_medium_latvian_ver2_pipeline", lang = "lv") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_medium_latvian_ver2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|lv| +|Size:|4.8 GB| + +## References + +https://huggingface.co/FelixK7/whisper-medium-lv-ver2 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_luluw_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_luluw_en.md new file mode 100644 index 00000000000000..5223b32fdc44c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_medium_luluw_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_medium_luluw WhisperForCTC from luluw +author: John Snow Labs +name: whisper_medium_luluw +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_medium_luluw` is a English model originally trained by luluw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_medium_luluw_en_5.5.1_3.0_1731306059271.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_medium_luluw_en_5.5.1_3.0_1731306059271.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("whisper_medium_luluw","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_medium_luluw", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_medium_luluw| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|4.8 GB| + +## References + +https://huggingface.co/luluw/whisper-medium \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_omg_hi.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_omg_hi.md new file mode 100644 index 00000000000000..b4435c02573f70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_omg_hi.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Hindi whisper_omg WhisperForCTC from nurzhanit +author: John Snow Labs +name: whisper_omg +date: 2024-11-11 +tags: [hi, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_omg` is a Hindi model originally trained by nurzhanit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_omg_hi_5.5.1_3.0_1731303196441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_omg_hi_5.5.1_3.0_1731303196441.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("whisper_omg","hi") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_omg", "hi") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_omg| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/nurzhanit/whisper-omg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_omg_pipeline_hi.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_omg_pipeline_hi.md new file mode 100644 index 00000000000000..ce99657ac4eb4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_omg_pipeline_hi.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Hindi whisper_omg_pipeline pipeline WhisperForCTC from nurzhanit +author: John Snow Labs +name: whisper_omg_pipeline +date: 2024-11-11 +tags: [hi, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_omg_pipeline` is a Hindi model originally trained by nurzhanit. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_omg_pipeline_hi_5.5.1_3.0_1731303281350.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_omg_pipeline_hi_5.5.1_3.0_1731303281350.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_omg_pipeline", lang = "hi") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_omg_pipeline", lang = "hi") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_omg_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/nurzhanit/whisper-omg + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_arabic_augmentation_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_arabic_augmentation_en.md new file mode 100644 index 00000000000000..f3ce10b617691e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_arabic_augmentation_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_small_arabic_augmentation WhisperForCTC from MohammedNasri +author: John Snow Labs +name: whisper_small_arabic_augmentation +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_arabic_augmentation` is a English model originally trained by MohammedNasri. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_augmentation_en_5.5.1_3.0_1731302625589.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_augmentation_en_5.5.1_3.0_1731302625589.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("whisper_small_arabic_augmentation","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_arabic_augmentation", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_arabic_augmentation| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/MohammedNasri/whisper_small_ar_augmentation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_arabic_augmentation_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_arabic_augmentation_pipeline_en.md new file mode 100644 index 00000000000000..ab9d01e35faf54 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_arabic_augmentation_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_arabic_augmentation_pipeline pipeline WhisperForCTC from MohammedNasri +author: John Snow Labs +name: whisper_small_arabic_augmentation_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_arabic_augmentation_pipeline` is a English model originally trained by MohammedNasri. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_augmentation_pipeline_en_5.5.1_3.0_1731302718291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_arabic_augmentation_pipeline_en_5.5.1_3.0_1731302718291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_arabic_augmentation_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_arabic_augmentation_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_arabic_augmentation_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/MohammedNasri/whisper_small_ar_augmentation + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_dutch_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_dutch_en.md new file mode 100644 index 00000000000000..a5606e6acd2baf --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_dutch_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_small_dutch WhisperForCTC from qmeeus +author: John Snow Labs +name: whisper_small_dutch +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_dutch` is a English model originally trained by qmeeus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_dutch_en_5.5.1_3.0_1731306172648.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_dutch_en_5.5.1_3.0_1731306172648.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("whisper_small_dutch","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_dutch", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_dutch| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/qmeeus/whisper-small-nl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_dutch_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_dutch_pipeline_en.md new file mode 100644 index 00000000000000..d355242f419804 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_dutch_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_dutch_pipeline pipeline WhisperForCTC from qmeeus +author: John Snow Labs +name: whisper_small_dutch_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_dutch_pipeline` is a English model originally trained by qmeeus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_dutch_pipeline_en_5.5.1_3.0_1731306257048.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_dutch_pipeline_en_5.5.1_3.0_1731306257048.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_dutch_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_dutch_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_dutch_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/qmeeus/whisper-small-nl + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_english_crossdelenna_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_english_crossdelenna_en.md new file mode 100644 index 00000000000000..fb907989258e1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_english_crossdelenna_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_small_english_crossdelenna WhisperForCTC from crossdelenna +author: John Snow Labs +name: whisper_small_english_crossdelenna +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_english_crossdelenna` is a English model originally trained by crossdelenna. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_english_crossdelenna_en_5.5.1_3.0_1731303622627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_english_crossdelenna_en_5.5.1_3.0_1731303622627.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("whisper_small_english_crossdelenna","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_english_crossdelenna", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_english_crossdelenna| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/crossdelenna/whisper-small.en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_english_crossdelenna_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_english_crossdelenna_pipeline_en.md new file mode 100644 index 00000000000000..d42e75e87eb373 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_english_crossdelenna_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_english_crossdelenna_pipeline pipeline WhisperForCTC from crossdelenna +author: John Snow Labs +name: whisper_small_english_crossdelenna_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_english_crossdelenna_pipeline` is a English model originally trained by crossdelenna. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_english_crossdelenna_pipeline_en_5.5.1_3.0_1731303710904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_english_crossdelenna_pipeline_en_5.5.1_3.0_1731303710904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_english_crossdelenna_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_english_crossdelenna_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_english_crossdelenna_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/crossdelenna/whisper-small.en + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_french_uncased_fr.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_french_uncased_fr.md new file mode 100644 index 00000000000000..9159fcdc8de494 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_french_uncased_fr.md @@ -0,0 +1,84 @@ +--- +layout: model +title: French whisper_small_french_uncased WhisperForCTC from qanastek +author: John Snow Labs +name: whisper_small_french_uncased +date: 2024-11-11 +tags: [fr, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: fr +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_french_uncased` is a French model originally trained by qanastek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_french_uncased_fr_5.5.1_3.0_1731305584943.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_french_uncased_fr_5.5.1_3.0_1731305584943.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("whisper_small_french_uncased","fr") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_french_uncased", "fr") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_french_uncased| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|fr| +|Size:|1.7 GB| + +## References + +https://huggingface.co/qanastek/whisper-small-french-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_french_uncased_pipeline_fr.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_french_uncased_pipeline_fr.md new file mode 100644 index 00000000000000..cc55101ed344f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_french_uncased_pipeline_fr.md @@ -0,0 +1,69 @@ +--- +layout: model +title: French whisper_small_french_uncased_pipeline pipeline WhisperForCTC from qanastek +author: John Snow Labs +name: whisper_small_french_uncased_pipeline +date: 2024-11-11 +tags: [fr, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: fr +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_french_uncased_pipeline` is a French model originally trained by qanastek. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_french_uncased_pipeline_fr_5.5.1_3.0_1731305678116.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_french_uncased_pipeline_fr_5.5.1_3.0_1731305678116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_french_uncased_pipeline", lang = "fr") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_french_uncased_pipeline", lang = "fr") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_french_uncased_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|1.7 GB| + +## References + +https://huggingface.co/qanastek/whisper-small-french-uncased + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_greek_modern_finetune_el.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_greek_modern_finetune_el.md new file mode 100644 index 00000000000000..2ea8aa8874664b --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_greek_modern_finetune_el.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Modern Greek (1453-) whisper_small_greek_modern_finetune WhisperForCTC from voxreality +author: John Snow Labs +name: whisper_small_greek_modern_finetune +date: 2024-11-11 +tags: [el, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: el +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_greek_modern_finetune` is a Modern Greek (1453-) model originally trained by voxreality. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_greek_modern_finetune_el_5.5.1_3.0_1731306201554.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_greek_modern_finetune_el_5.5.1_3.0_1731306201554.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("whisper_small_greek_modern_finetune","el") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_greek_modern_finetune", "el") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_greek_modern_finetune| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|el| +|Size:|1.7 GB| + +## References + +https://huggingface.co/voxreality/whisper-small-el-finetune \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_greek_modern_finetune_pipeline_el.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_greek_modern_finetune_pipeline_el.md new file mode 100644 index 00000000000000..5c89a54dbbd1e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_greek_modern_finetune_pipeline_el.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Modern Greek (1453-) whisper_small_greek_modern_finetune_pipeline pipeline WhisperForCTC from voxreality +author: John Snow Labs +name: whisper_small_greek_modern_finetune_pipeline +date: 2024-11-11 +tags: [el, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: el +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_greek_modern_finetune_pipeline` is a Modern Greek (1453-) model originally trained by voxreality. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_greek_modern_finetune_pipeline_el_5.5.1_3.0_1731306288945.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_greek_modern_finetune_pipeline_el_5.5.1_3.0_1731306288945.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_greek_modern_finetune_pipeline", lang = "el") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_greek_modern_finetune_pipeline", lang = "el") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_greek_modern_finetune_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|el| +|Size:|1.7 GB| + +## References + +https://huggingface.co/voxreality/whisper-small-el-finetune + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_malay_my.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_malay_my.md new file mode 100644 index 00000000000000..9b5ba542689f6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_malay_my.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Burmese whisper_small_malay WhisperForCTC from M00dler +author: John Snow Labs +name: whisper_small_malay +date: 2024-11-11 +tags: [my, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: my +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_malay` is a Burmese model originally trained by M00dler. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_malay_my_5.5.1_3.0_1731303130517.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_malay_my_5.5.1_3.0_1731303130517.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("whisper_small_malay","my") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_malay", "my") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_malay| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|my| +|Size:|1.7 GB| + +## References + +https://huggingface.co/M00dler/whisper-small-malay \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_malay_pipeline_my.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_malay_pipeline_my.md new file mode 100644 index 00000000000000..cd4e74b027787f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_malay_pipeline_my.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Burmese whisper_small_malay_pipeline pipeline WhisperForCTC from M00dler +author: John Snow Labs +name: whisper_small_malay_pipeline +date: 2024-11-11 +tags: [my, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: my +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_malay_pipeline` is a Burmese model originally trained by M00dler. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_malay_pipeline_my_5.5.1_3.0_1731303216891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_malay_pipeline_my_5.5.1_3.0_1731303216891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_malay_pipeline", lang = "my") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_malay_pipeline", lang = "my") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_malay_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|my| +|Size:|1.7 GB| + +## References + +https://huggingface.co/M00dler/whisper-small-malay + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_russian_f_pipeline_ru.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_russian_f_pipeline_ru.md new file mode 100644 index 00000000000000..5a1606ef225ed4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_russian_f_pipeline_ru.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Russian whisper_small_russian_f_pipeline pipeline WhisperForCTC from Garon16 +author: John Snow Labs +name: whisper_small_russian_f_pipeline +date: 2024-11-11 +tags: [ru, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_russian_f_pipeline` is a Russian model originally trained by Garon16. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_russian_f_pipeline_ru_5.5.1_3.0_1731304185329.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_russian_f_pipeline_ru_5.5.1_3.0_1731304185329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_russian_f_pipeline", lang = "ru") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_russian_f_pipeline", lang = "ru") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_russian_f_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ru| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Garon16/whisper_small_ru_f + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_russian_f_ru.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_russian_f_ru.md new file mode 100644 index 00000000000000..9bc6ca2f6fa1a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_russian_f_ru.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Russian whisper_small_russian_f WhisperForCTC from Garon16 +author: John Snow Labs +name: whisper_small_russian_f +date: 2024-11-11 +tags: [ru, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: ru +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_russian_f` is a Russian model originally trained by Garon16. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_russian_f_ru_5.5.1_3.0_1731304097971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_russian_f_ru_5.5.1_3.0_1731304097971.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("whisper_small_russian_f","ru") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_russian_f", "ru") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_russian_f| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ru| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Garon16/whisper_small_ru_f \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_western_frisian_dutch_transfer_from_english_fy.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_western_frisian_dutch_transfer_from_english_fy.md new file mode 100644 index 00000000000000..6693aa1ec38031 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_western_frisian_dutch_transfer_from_english_fy.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Western Frisian whisper_small_western_frisian_dutch_transfer_from_english WhisperForCTC from polixonrio +author: John Snow Labs +name: whisper_small_western_frisian_dutch_transfer_from_english +date: 2024-11-11 +tags: [fy, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: fy +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_western_frisian_dutch_transfer_from_english` is a Western Frisian model originally trained by polixonrio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_western_frisian_dutch_transfer_from_english_fy_5.5.1_3.0_1731303370187.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_western_frisian_dutch_transfer_from_english_fy_5.5.1_3.0_1731303370187.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("whisper_small_western_frisian_dutch_transfer_from_english","fy") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_western_frisian_dutch_transfer_from_english", "fy") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_western_frisian_dutch_transfer_from_english| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|fy| +|Size:|1.7 GB| + +## References + +https://huggingface.co/polixonrio/whisper-small-fy-NL-Transfer-From-English \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_western_frisian_dutch_transfer_from_english_pipeline_fy.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_western_frisian_dutch_transfer_from_english_pipeline_fy.md new file mode 100644 index 00000000000000..b27ca32dd1b612 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_western_frisian_dutch_transfer_from_english_pipeline_fy.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Western Frisian whisper_small_western_frisian_dutch_transfer_from_english_pipeline pipeline WhisperForCTC from polixonrio +author: John Snow Labs +name: whisper_small_western_frisian_dutch_transfer_from_english_pipeline +date: 2024-11-11 +tags: [fy, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: fy +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_western_frisian_dutch_transfer_from_english_pipeline` is a Western Frisian model originally trained by polixonrio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_western_frisian_dutch_transfer_from_english_pipeline_fy_5.5.1_3.0_1731303454310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_western_frisian_dutch_transfer_from_english_pipeline_fy_5.5.1_3.0_1731303454310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_western_frisian_dutch_transfer_from_english_pipeline", lang = "fy") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_western_frisian_dutch_transfer_from_english_pipeline", lang = "fy") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_western_frisian_dutch_transfer_from_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|fy| +|Size:|1.7 GB| + +## References + +https://huggingface.co/polixonrio/whisper-small-fy-NL-Transfer-From-English + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_yt_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_yt_en.md new file mode 100644 index 00000000000000..47394fac83daa2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_yt_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_small_yt WhisperForCTC from PatrickML +author: John Snow Labs +name: whisper_small_yt +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_yt` is a English model originally trained by PatrickML. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_yt_en_5.5.1_3.0_1731304188617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_yt_en_5.5.1_3.0_1731304188617.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("whisper_small_yt","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_small_yt", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_yt| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/PatrickML/whisper_small_yt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_small_yt_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_yt_pipeline_en.md new file mode 100644 index 00000000000000..0418dc7ef2e35e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_small_yt_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_small_yt_pipeline pipeline WhisperForCTC from PatrickML +author: John Snow Labs +name: whisper_small_yt_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_small_yt_pipeline` is a English model originally trained by PatrickML. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_small_yt_pipeline_en_5.5.1_3.0_1731304293862.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_small_yt_pipeline_en_5.5.1_3.0_1731304293862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_small_yt_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_small_yt_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_small_yt_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/PatrickML/whisper_small_yt + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_amharic_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_amharic_en.md new file mode 100644 index 00000000000000..27666684376da2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_amharic_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_tiny_amharic WhisperForCTC from Gizachew +author: John Snow Labs +name: whisper_tiny_amharic +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_amharic` is a English model originally trained by Gizachew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_amharic_en_5.5.1_3.0_1731302156104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_amharic_en_5.5.1_3.0_1731302156104.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("whisper_tiny_amharic","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_tiny_amharic", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_amharic| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|390.2 MB| + +## References + +https://huggingface.co/Gizachew/whisper-tiny-amharic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_amharic_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_amharic_pipeline_en.md new file mode 100644 index 00000000000000..9c1d7e76a23b07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_amharic_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_tiny_amharic_pipeline pipeline WhisperForCTC from Gizachew +author: John Snow Labs +name: whisper_tiny_amharic_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_amharic_pipeline` is a English model originally trained by Gizachew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_amharic_pipeline_en_5.5.1_3.0_1731302179868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_amharic_pipeline_en_5.5.1_3.0_1731302179868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_tiny_amharic_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_tiny_amharic_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_amharic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.2 MB| + +## References + +https://huggingface.co/Gizachew/whisper-tiny-amharic + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_arabic_ar.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_arabic_ar.md new file mode 100644 index 00000000000000..3d4c57db055fc6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_arabic_ar.md @@ -0,0 +1,84 @@ +--- +layout: model +title: Arabic whisper_tiny_arabic WhisperForCTC from Yassinevic +author: John Snow Labs +name: whisper_tiny_arabic +date: 2024-11-11 +tags: [ar, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: ar +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_arabic` is a Arabic model originally trained by Yassinevic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_arabic_ar_5.5.1_3.0_1731302665054.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_arabic_ar_5.5.1_3.0_1731302665054.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("whisper_tiny_arabic","ar") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_tiny_arabic", "ar") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_arabic| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ar| +|Size:|389.9 MB| + +## References + +https://huggingface.co/Yassinevic/whisper-tiny-ar \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_arabic_pipeline_ar.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_arabic_pipeline_ar.md new file mode 100644 index 00000000000000..9f24da1fd6d8e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_arabic_pipeline_ar.md @@ -0,0 +1,69 @@ +--- +layout: model +title: Arabic whisper_tiny_arabic_pipeline pipeline WhisperForCTC from Yassinevic +author: John Snow Labs +name: whisper_tiny_arabic_pipeline +date: 2024-11-11 +tags: [ar, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: ar +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_arabic_pipeline` is a Arabic model originally trained by Yassinevic. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_arabic_pipeline_ar_5.5.1_3.0_1731302688987.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_arabic_pipeline_ar_5.5.1_3.0_1731302688987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_tiny_arabic_pipeline", lang = "ar") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_tiny_arabic_pipeline", lang = "ar") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|ar| +|Size:|389.9 MB| + +## References + +https://huggingface.co/Yassinevic/whisper-tiny-ar + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_chinese_antares28_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_chinese_antares28_en.md new file mode 100644 index 00000000000000..2ced5bce8795dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_chinese_antares28_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_tiny_chinese_antares28 WhisperForCTC from Antares28 +author: John Snow Labs +name: whisper_tiny_chinese_antares28 +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_chinese_antares28` is a English model originally trained by Antares28. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_chinese_antares28_en_5.5.1_3.0_1731305756005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_chinese_antares28_en_5.5.1_3.0_1731305756005.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("whisper_tiny_chinese_antares28","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_tiny_chinese_antares28", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_chinese_antares28| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|389.9 MB| + +## References + +https://huggingface.co/Antares28/whisper-tiny-zh \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_chinese_antares28_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_chinese_antares28_pipeline_en.md new file mode 100644 index 00000000000000..870ef5a471d8f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_chinese_antares28_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_tiny_chinese_antares28_pipeline pipeline WhisperForCTC from Antares28 +author: John Snow Labs +name: whisper_tiny_chinese_antares28_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_chinese_antares28_pipeline` is a English model originally trained by Antares28. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_chinese_antares28_pipeline_en_5.5.1_3.0_1731305777373.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_chinese_antares28_pipeline_en_5.5.1_3.0_1731305777373.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_tiny_chinese_antares28_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_tiny_chinese_antares28_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_chinese_antares28_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|389.9 MB| + +## References + +https://huggingface.co/Antares28/whisper-tiny-zh + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_nob_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_nob_en.md new file mode 100644 index 00000000000000..1a9a08d9d62c8a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_nob_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_tiny_nob WhisperForCTC from NbAiLab +author: John Snow Labs +name: whisper_tiny_nob +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_nob` is a English model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_nob_en_5.5.1_3.0_1731303096066.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_nob_en_5.5.1_3.0_1731303096066.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("whisper_tiny_nob","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_tiny_nob", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_nob| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|390.8 MB| + +## References + +https://huggingface.co/NbAiLab/whisper-tiny-nob \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_nob_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_nob_pipeline_en.md new file mode 100644 index 00000000000000..16a1fec2c833c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_nob_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_tiny_nob_pipeline pipeline WhisperForCTC from NbAiLab +author: John Snow Labs +name: whisper_tiny_nob_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_nob_pipeline` is a English model originally trained by NbAiLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_nob_pipeline_en_5.5.1_3.0_1731303117221.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_nob_pipeline_en_5.5.1_3.0_1731303117221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_tiny_nob_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_tiny_nob_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_nob_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.8 MB| + +## References + +https://huggingface.co/NbAiLab/whisper-tiny-nob + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_v2_2_romanian_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_v2_2_romanian_en.md new file mode 100644 index 00000000000000..fa824e6d0d9ca6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_v2_2_romanian_en.md @@ -0,0 +1,84 @@ +--- +layout: model +title: English whisper_tiny_v2_2_romanian WhisperForCTC from giigii91 +author: John Snow Labs +name: whisper_tiny_v2_2_romanian +date: 2024-11-11 +tags: [en, open_source, onnx, asr, whisper] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_v2_2_romanian` is a English model originally trained by giigii91. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_v2_2_romanian_en_5.5.1_3.0_1731302411636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_v2_2_romanian_en_5.5.1_3.0_1731302411636.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("whisper_tiny_v2_2_romanian","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new DocumentAssembler() + .setInputCols("audio_content") + .setOutputCols("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("whisper_tiny_v2_2_romanian", "en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, speechToText)) +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_v2_2_romanian| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|374.7 MB| + +## References + +https://huggingface.co/giigii91/whisper-tiny_v2.2-ro \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_v2_2_romanian_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_v2_2_romanian_pipeline_en.md new file mode 100644 index 00000000000000..9ee97f1589783a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-whisper_tiny_v2_2_romanian_pipeline_en.md @@ -0,0 +1,69 @@ +--- +layout: model +title: English whisper_tiny_v2_2_romanian_pipeline pipeline WhisperForCTC from giigii91 +author: John Snow Labs +name: whisper_tiny_v2_2_romanian_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +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.`whisper_tiny_v2_2_romanian_pipeline` is a English model originally trained by giigii91. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/whisper_tiny_v2_2_romanian_pipeline_en_5.5.1_3.0_1731302438168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/whisper_tiny_v2_2_romanian_pipeline_en_5.5.1_3.0_1731302438168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("whisper_tiny_v2_2_romanian_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("whisper_tiny_v2_2_romanian_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|whisper_tiny_v2_2_romanian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|374.7 MB| + +## References + +https://huggingface.co/giigii91/whisper-tiny_v2.2-ro + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-workprocess_24_10_01_en.md b/docs/_posts/ahmedlone127/2024-11-11-workprocess_24_10_01_en.md new file mode 100644 index 00000000000000..4b669d94a3965f --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-workprocess_24_10_01_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English workprocess_24_10_01 BertForSequenceClassification from shshin0317 +author: John Snow Labs +name: workprocess_24_10_01 +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, bert] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`workprocess_24_10_01` is a English model originally trained by shshin0317. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/workprocess_24_10_01_en_5.5.1_3.0_1731309636847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/workprocess_24_10_01_en_5.5.1_3.0_1731309636847.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("workprocess_24_10_01","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("workprocess_24_10_01", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|workprocess_24_10_01| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.9 MB| + +## References + +https://huggingface.co/shshin0317/workprocess_24_10_01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-workprocess_24_10_01_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-workprocess_24_10_01_pipeline_en.md new file mode 100644 index 00000000000000..76ac4fd47a25ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-workprocess_24_10_01_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English workprocess_24_10_01_pipeline pipeline BertForSequenceClassification from shshin0317 +author: John Snow Labs +name: workprocess_24_10_01_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`workprocess_24_10_01_pipeline` is a English model originally trained by shshin0317. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/workprocess_24_10_01_pipeline_en_5.5.1_3.0_1731309664028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/workprocess_24_10_01_pipeline_en_5.5.1_3.0_1731309664028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("workprocess_24_10_01_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("workprocess_24_10_01_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|workprocess_24_10_01_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|414.9 MB| + +## References + +https://huggingface.co/shshin0317/workprocess_24_10_01 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- BertForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_cebinary_vmo2_large_3_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_cebinary_vmo2_large_3_en.md new file mode 100644 index 00000000000000..0304b680ab9936 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_cebinary_vmo2_large_3_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_cebinary_vmo2_large_3 MPNetForSequenceClassification from enochlev +author: John Snow Labs +name: xlm_cebinary_vmo2_large_3 +date: 2024-11-11 +tags: [en, open_source, onnx, sequence_classification, mpnet] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: MPNetForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_cebinary_vmo2_large_3` is a English model originally trained by enochlev. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_cebinary_vmo2_large_3_en_5.5.1_3.0_1731301250606.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_cebinary_vmo2_large_3_en_5.5.1_3.0_1731301250606.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 = MPNetForSequenceClassification.pretrained("xlm_cebinary_vmo2_large_3","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("class") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, sequenceClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier = MPNetForSequenceClassification.pretrained("xlm_cebinary_vmo2_large_3", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_cebinary_vmo2_large_3| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/enochlev/XLM-CEBinary-VMO2-large-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_cebinary_vmo2_large_3_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_cebinary_vmo2_large_3_pipeline_en.md new file mode 100644 index 00000000000000..e5ae9d36ca4bd9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_cebinary_vmo2_large_3_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_cebinary_vmo2_large_3_pipeline pipeline MPNetForSequenceClassification from enochlev +author: John Snow Labs +name: xlm_cebinary_vmo2_large_3_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained MPNetForSequenceClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_cebinary_vmo2_large_3_pipeline` is a English model originally trained by enochlev. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_cebinary_vmo2_large_3_pipeline_en_5.5.1_3.0_1731301272226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_cebinary_vmo2_large_3_pipeline_en_5.5.1_3.0_1731301272226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_cebinary_vmo2_large_3_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_cebinary_vmo2_large_3_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_cebinary_vmo2_large_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/enochlev/XLM-CEBinary-VMO2-large-3 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- MPNetForSequenceClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_conll2003_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_conll2003_en.md new file mode 100644 index 00000000000000..f08eb1efd9d2ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_conll2003_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_conll2003 XlmRoBertaForTokenClassification from Amir13 +author: John Snow Labs +name: xlm_roberta_base_conll2003 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_conll2003` is a English model originally trained by Amir13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_conll2003_en_5.5.1_3.0_1731293705042.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_conll2003_en_5.5.1_3.0_1731293705042.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') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_conll2003","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_conll2003", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_conll2003| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|843.4 MB| + +## References + +https://huggingface.co/Amir13/xlm-roberta-base-conll2003 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_conll2003_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_conll2003_pipeline_en.md new file mode 100644 index 00000000000000..97ba29a24389e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_conll2003_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_conll2003_pipeline pipeline XlmRoBertaForTokenClassification from Amir13 +author: John Snow Labs +name: xlm_roberta_base_conll2003_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_conll2003_pipeline` is a English model originally trained by Amir13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_conll2003_pipeline_en_5.5.1_3.0_1731293773356.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_conll2003_pipeline_en_5.5.1_3.0_1731293773356.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_conll2003_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_conll2003_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_conll2003_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|843.4 MB| + +## References + +https://huggingface.co/Amir13/xlm-roberta-base-conll2003 + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_en.md new file mode 100644 index 00000000000000..857973173c127a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_0ppxnhximxr XlmRoBertaForTokenClassification from 0ppxnhximxr +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_0ppxnhximxr +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_0ppxnhximxr` is a English model originally trained by 0ppxnhximxr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_en_5.5.1_3.0_1731293742525.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_en_5.5.1_3.0_1731293742525.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') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_0ppxnhximxr","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_0ppxnhximxr", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_0ppxnhximxr| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|840.8 MB| + +## References + +https://huggingface.co/0ppxnhximxr/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline_en.md new file mode 100644 index 00000000000000..e5f51a292de85e --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline pipeline XlmRoBertaForTokenClassification from 0ppxnhximxr +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline` is a English model originally trained by 0ppxnhximxr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline_en_5.5.1_3.0_1731293829031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline_en_5.5.1_3.0_1731293829031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_0ppxnhximxr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|840.8 MB| + +## References + +https://huggingface.co/0ppxnhximxr/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_skr3178_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_skr3178_en.md new file mode 100644 index 00000000000000..713a4393c505a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_skr3178_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_skr3178 XlmRoBertaForTokenClassification from skr3178 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_skr3178 +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_skr3178` is a English model originally trained by skr3178. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_skr3178_en_5.5.1_3.0_1731293331803.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_skr3178_en_5.5.1_3.0_1731293331803.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') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_skr3178","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_roberta_base_finetuned_panx_german_skr3178", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_skr3178| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/skr3178/xlm-roberta-base-finetuned-panx-de \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_skr3178_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_skr3178_pipeline_en.md new file mode 100644 index 00000000000000..a392c47aa99014 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_roberta_base_finetuned_panx_german_skr3178_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_roberta_base_finetuned_panx_german_skr3178_pipeline pipeline XlmRoBertaForTokenClassification from skr3178 +author: John Snow Labs +name: xlm_roberta_base_finetuned_panx_german_skr3178_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_roberta_base_finetuned_panx_german_skr3178_pipeline` is a English model originally trained by skr3178. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_skr3178_pipeline_en_5.5.1_3.0_1731293402415.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_roberta_base_finetuned_panx_german_skr3178_pipeline_en_5.5.1_3.0_1731293402415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_skr3178_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_roberta_base_finetuned_panx_german_skr3178_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_roberta_base_finetuned_panx_german_skr3178_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|853.8 MB| + +## References + +https://huggingface.co/skr3178/xlm-roberta-base-finetuned-panx-de + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_word_shopsign_pretrained_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_word_shopsign_pretrained_en.md new file mode 100644 index 00000000000000..fee4f4bd6ab09a --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_word_shopsign_pretrained_en.md @@ -0,0 +1,94 @@ +--- +layout: model +title: English xlm_word_shopsign_pretrained XlmRoBertaForTokenClassification from HyungYoun +author: John Snow Labs +name: xlm_word_shopsign_pretrained +date: 2024-11-11 +tags: [en, open_source, onnx, token_classification, xlm_roberta, ner] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +engine: onnx +annotator: XlmRoBertaForTokenClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_word_shopsign_pretrained` is a English model originally trained by HyungYoun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_word_shopsign_pretrained_en_5.5.1_3.0_1731293658556.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_word_shopsign_pretrained_en_5.5.1_3.0_1731293658556.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') + +tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_word_shopsign_pretrained","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("ner") + +pipeline = Pipeline().setStages([documentAssembler, tokenizer, tokenClassifier]) +data = spark.createDataFrame([["I love spark-nlp"]]).toDF("text") +pipelineModel = pipeline.fit(data) +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val documentAssembler = new DocumentAssembler() + .setInputCols("text") + .setOutputCols("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val tokenClassifier = XlmRoBertaForTokenClassification.pretrained("xlm_word_shopsign_pretrained", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, tokenClassifier)) +val data = Seq("I love spark-nlp").toDS.toDF("text") +val pipelineModel = pipeline.fit(data) +val pipelineDF = pipelineModel.transform(data) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_word_shopsign_pretrained| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|794.3 MB| + +## References + +https://huggingface.co/HyungYoun/xlm-word-shopsign-pretrained \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2024-11-11-xlm_word_shopsign_pretrained_pipeline_en.md b/docs/_posts/ahmedlone127/2024-11-11-xlm_word_shopsign_pretrained_pipeline_en.md new file mode 100644 index 00000000000000..7315a5c1e26498 --- /dev/null +++ b/docs/_posts/ahmedlone127/2024-11-11-xlm_word_shopsign_pretrained_pipeline_en.md @@ -0,0 +1,70 @@ +--- +layout: model +title: English xlm_word_shopsign_pretrained_pipeline pipeline XlmRoBertaForTokenClassification from HyungYoun +author: John Snow Labs +name: xlm_word_shopsign_pretrained_pipeline +date: 2024-11-11 +tags: [en, open_source, pipeline, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.5.1 +spark_version: 3.0 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained XlmRoBertaForTokenClassification, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_word_shopsign_pretrained_pipeline` is a English model originally trained by HyungYoun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_word_shopsign_pretrained_pipeline_en_5.5.1_3.0_1731293795355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_word_shopsign_pretrained_pipeline_en_5.5.1_3.0_1731293795355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline("xlm_word_shopsign_pretrained_pipeline", lang = "en") +annotations = pipeline.transform(df) + +``` +```scala + +val pipeline = new PretrainedPipeline("xlm_word_shopsign_pretrained_pipeline", lang = "en") +val annotations = pipeline.transform(df) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_word_shopsign_pretrained_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.5.1+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|794.3 MB| + +## References + +https://huggingface.co/HyungYoun/xlm-word-shopsign-pretrained + +## Included Models + +- DocumentAssembler +- TokenizerModel +- XlmRoBertaForTokenClassification \ No newline at end of file diff --git a/docs/_posts/danilojsl/2024-10-03-blip_vqa_base_en.md b/docs/_posts/danilojsl/2024-10-03-blip_vqa_base_en.md new file mode 100644 index 00000000000000..798005ef178919 --- /dev/null +++ b/docs/_posts/danilojsl/2024-10-03-blip_vqa_base_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: BLIP Question Answering +author: John Snow Labs +name: blip_vqa_base +date: 2024-10-03 +tags: [en, open_source, tensorflow] +task: Question Answering +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.4 +supported: true +engine: tensorflow +annotator: BLIPForQuestionAnswering +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +BLIP Model for visual question answering. The model consists of a vision encoder, a text encoder as well as a text decoder. The vision encoder will encode the input image, the text encoder will encode the input question together with the encoding of the image, and the text decoder will output the answer to the question. + +## Predicted Entities + + + +{:.btn-box} + +[Open in Colab](https://github.com/JohnSnowLabs/spark-nlp/blob/master/examples/python/transformers/HuggingFace_in_Spark_NLP_BLIPForQuestionAnswering.ipynb){:.button.button-orange.button-orange-trans.co.button-icon} +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/blip_vqa_base_en_5.5.0_3.4_1727997969354.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/blip_vqa_base_en_5.5.0_3.4_1727997969354.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + +To proceed, please create a DataFrame with two columns: + +- An image column that contains the file path for each image in the directory. +- A text column where you can input the specific question you would like to ask about each image. + +For example: + +```python +from pyspark.sql.functions import lit + +images_path = "./images/" +image_df = spark.read.format("image").load(path=images_path) + +test_df = image_df.withColumn("text", lit("What's this picture about?")) +test_df.show() +``` + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +imageAssembler = ImageAssembler() \ + .setInputCol("image") \ + .setOutputCol("image_assembler") \ + +imageClassifier = BLIPForQuestionAnswering.load("./{}_spark_nlp".format(MODEL_NAME)) \ + .setInputCols("image_assembler") \ + .setOutputCol("answer") \ + .setSize(384) + +pipeline = Pipeline( + stages=[ + imageAssembler, + imageClassifier, + ] +) + +model = pipeline.fit(test_df) +result = model.transform(test_df) +result.select("image_assembler.origin", "answer.result").show(truncate = False) +``` +```scala +val imageAssembler: ImageAssembler = new ImageAssembler() + .setInputCol("image") + .setOutputCol("image_assembler") + +val loadModel = BLIPForQuestionAnswering + .pretrained() + .setInputCols("image_assembler") + .setOutputCol("answer") + .setSize(384) + +val newPipeline: Pipeline = + new Pipeline().setStages(Array(imageAssembler, loadModel)) + +newPipeline.fit(testDF) +val result = model.transform(testDF) + +result.select("image_assembler.origin", "answer.result").show(truncate = false) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|blip_vqa_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.4 GB| \ No newline at end of file diff --git a/docs/_posts/gadde5300/2024-11-13-roberta_embeddings_legal_roberta_base_en.md b/docs/_posts/gadde5300/2024-11-13-roberta_embeddings_legal_roberta_base_en.md new file mode 100644 index 00000000000000..77ef36bb4ee436 --- /dev/null +++ b/docs/_posts/gadde5300/2024-11-13-roberta_embeddings_legal_roberta_base_en.md @@ -0,0 +1,109 @@ +--- +layout: model +title: English Legal RoBERTa Embeddings (CaseLaw, Base, Cased) +author: John Snow Labs +name: roberta_embeddings_legal_roberta_base +date: 2024-11-13 +tags: [roberta, embeddings, en, open_source, tensorflow] +task: Embeddings +language: en +edition: Spark NLP 5.5.0 +spark_version: 3.0 +supported: true +engine: tensorflow +annotator: RoBertaEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained Legal RoBERTa Embeddings model, uploaded to Hugging Face, adapted and imported into Spark NLP. `legal-roberta-base` is a English model orginally trained by `saibo`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_embeddings_legal_roberta_base_en_5.5.0_3.0_1731462634993.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_embeddings_legal_roberta_base_en_5.5.0_3.0_1731462634993.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") + +embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_legal_roberta_base","en") \ +.setInputCols(["document", "token"]) \ +.setOutputCol("embeddings") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings]) + +data = spark.createDataFrame([["I love 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 embeddings = RoBertaEmbeddings.pretrained("roberta_embeddings_legal_roberta_base","en") +.setInputCols(Array("document", "token")) +.setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings)) + +val data = Seq("I love Spark NLP").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.embed.legal_roberta_base").predict("""I love Spark NLP""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_embeddings_legal_roberta_base| +|Compatibility:|Spark NLP 5.5.0+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[sentence, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|468.9 MB| +|Case sensitive:|true| + +## Benchmarking + +```bash +- https://huggingface.co/saibo/legal-roberta-base +- https://www.kaggle.com/uspto/patent-litigations +- https://case.law/ +- https://www.kaggle.com/bigquery/patents +- https://www.kaggle.com/sohier/beyond-queries-exploring-the-bigquery-api +``` \ No newline at end of file