2024-12-16-bert_base_chinese_finetuned_cmrc2018_pipeline_en

docs/_posts/ahmedlone127/2024-12-15-bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1_en.md

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+---
+layout: model
+title: English bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1 MPNetEmbeddings from abhijitt
+author: John Snow Labs
+name: bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1
+date: 2024-12-15
+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.`bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1` is a English model originally trained by abhijitt.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1_en_5.5.1_3.0_1734306042809.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1_en_5.5.1_3.0_1734306042809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+embeddings = MPNetEmbeddings.pretrained("bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1","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("bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1","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)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_southern_sotho_qa_multi_qa_mpnet_base_dot_v1_epochs_1|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[mpnet]|
+|Language:|en|
+|Size:|407.0 MB|
+
+## References
+
+https://huggingface.co/abhijitt/bert_st_qa_multi-qa-mpnet-base-dot-v1-epochs-1

docs/_posts/ahmedlone127/2024-12-15-results_glebnonegolubin_pipeline_en.md

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+---
+layout: model
+title: English results_glebnonegolubin_pipeline pipeline T5Transformer from GlebNoNeGolubin
+author: John Snow Labs
+name: results_glebnonegolubin_pipeline
+date: 2024-12-15
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+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 T5Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`results_glebnonegolubin_pipeline` is a English model originally trained by GlebNoNeGolubin.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/results_glebnonegolubin_pipeline_en_5.5.1_3.0_1734301468191.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/results_glebnonegolubin_pipeline_en_5.5.1_3.0_1734301468191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("results_glebnonegolubin_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("results_glebnonegolubin_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|results_glebnonegolubin_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|349.8 MB|
+
+## References
+
+https://huggingface.co/GlebNoNeGolubin/results
+
+## Included Models
+
+- DocumentAssembler
+- T5Transformer

docs/_posts/ahmedlone127/2024-12-16-256_5epoch_en.md

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+---
+layout: model
+title: English 256_5epoch GPT2Transformer from Corianas
+author: John Snow Labs
+name: 256_5epoch
+date: 2024-12-16
+tags: [en, open_source, onnx, text_generation, gpt2]
+task: [Question Answering, Summarization, Translation, Text Generation]
+language: en
+edition: Spark NLP 5.5.1
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: GPT2Transformer
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained GPT2Transformer model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`256_5epoch` is a English model originally trained by Corianas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/256_5epoch_en_5.5.1_3.0_1734388628329.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/256_5epoch_en_5.5.1_3.0_1734388628329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+documentAssembler = DocumentAssembler() \
+      .setInputCol("text") \
+      .setOutputCol("document")
+
+seq2seq = GPT2Transformer.pretrained("256_5epoch","en") \
+      .setInputCols(["documents"]) \
+      .setOutputCol("generation")       
+
+pipeline = Pipeline().setStages([documentAssembler, seq2seq])
+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 seq2seq = GPT2Transformer.pretrained("256_5epoch","en") 
+    .setInputCols(Array("documents")) 
+    .setOutputCol("generation")
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, seq2seq))
+val data = Seq("I love spark-nlp").toDF("text")
+val pipelineModel = pipeline.fit(data)
+val pipelineDF = pipelineModel.transform(data)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|256_5epoch|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document]|
+|Output Labels:|[generation]|
+|Language:|en|
+|Size:|592.8 MB|
+
+## References
+
+https://huggingface.co/Corianas/256_5epoch

docs/_posts/ahmedlone127/2024-12-16-256_5epoch_pipeline_en.md

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+---
+layout: model
+title: English 256_5epoch_pipeline pipeline GPT2Transformer from Corianas
+author: John Snow Labs
+name: 256_5epoch_pipeline
+date: 2024-12-16
+tags: [en, open_source, pipeline, onnx]
+task: [Question Answering, Summarization, Translation, Text Generation]
+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 GPT2Transformer, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`256_5epoch_pipeline` is a English model originally trained by Corianas.
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/256_5epoch_pipeline_en_5.5.1_3.0_1734388817992.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/256_5epoch_pipeline_en_5.5.1_3.0_1734388817992.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+
+pipeline = PretrainedPipeline("256_5epoch_pipeline", lang = "en")
+annotations =  pipeline.transform(df)   
+
+```
+```scala
+
+val pipeline = new PretrainedPipeline("256_5epoch_pipeline", lang = "en")
+val annotations = pipeline.transform(df)
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|256_5epoch_pipeline|
+|Type:|pipeline|
+|Compatibility:|Spark NLP 5.5.1+|
+|License:|Open Source|
+|Edition:|Official|
+|Language:|en|
+|Size:|592.8 MB|
+
+## References
+
+https://huggingface.co/Corianas/256_5epoch
+
+## Included Models
+
+- DocumentAssembler
+- GPT2Transformer