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  • John Snow Labs
  • Apr 05, 2023

English BertForQuestionAnswering Cased model (from mrm8488)

  • en
  • open_source
  • bert
  • question_answering
  • tensorflow

Description

Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-medium-finetuned-squadv2 is a English model originally trained by mrm8488.

Download Copy S3 URI

How to use

Document_Assembler = MultiDocumentAssembler()\
     .setInputCols(["question", "context"])\
     .setOutputCols(["document_question", "document_context"])

Question_Answering = BertForQuestionAnswering.pretrained("Bert_qa_medium_finetuned_squadv2","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)

val Document_Assembler = new MultiDocumentAssembler()
     .setInputCols(Array("question", "context"))
     .setOutputCols(Array("document_question", "document_context"))

val Question_Answering = BertForQuestionAnswering.pretrained("Bert_qa_medium_finetuned_squadv2","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 Information

Model Name: Bert_qa_medium_finetuned_squadv2
Compatibility: Spark NLP 4.4.0+
License: Open Source
Edition: Official
Input Labels: [document_question, document_context]
Output Labels: [answer]
Language: en
Size: 154.6 MB
Case sensitive: true
Max sentence length: 512

References

  • https://huggingface.co/mrm8488/bert-medium-finetuned-squadv2
  • https://github.com/google-research/bert/
  • https://github.com/google-research
  • https://rajpurkar.github.io/SQuAD-explorer/
  • https://arxiv.org/abs/1908.08962
  • https://rajpurkar.github.io/SQuAD-explorer/
  • https://twitter.com/mrm8488
  • https://www.linkedin.com/in/manuel-romero-cs/