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  • John Snow Labs
  • Nov 17, 2023

English adl2023_hw1_span_selection BertForQuestionAnswering from dean22029

  • bert
  • en
  • open_source
  • question_answering
  • onnx

Description

Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.adl2023_hw1_span_selection is a English model originally trained by dean22029.

Download Copy S3 URI

How to use



document_assembler = MultiDocumentAssembler() \
    .setInputCol(["question", "context"]) \
    .setOutputCol(["document_question", "document_context"])
    
    
spanClassifier = BertForQuestionAnswering.pretrained("adl2023_hw1_span_selection","en") \
            .setInputCols(["document_question","document_context"]) \
            .setOutputCol("answer")

pipeline = Pipeline().setStages([document_assembler, spanClassifier])

pipelineModel = pipeline.fit(data)

pipelineDF = pipelineModel.transform(data)




val document_assembler = new MultiDocumentAssembler()
    .setInputCol(Array("question", "context")) 
    .setOutputCol(Array("document_question", "document_context"))
    
val spanClassifier = BertForQuestionAnswering  
    .pretrained("adl2023_hw1_span_selection", "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 Information

Model Name: adl2023_hw1_span_selection
Compatibility: Spark NLP 5.2.0+
License: Open Source
Edition: Official
Input Labels: [document_question, document_context]
Output Labels: [answer]
Language: en
Size: 1.2 GB

References

https://huggingface.co/dean22029/adl2023_hw1_span_selection