Catalan RobertaForQuestionAnswering (from projecte-aina)

Description

Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. roberta-base-ca-cased-qa is a Catalan model originally trained by projecte-aina.

Download Copy S3 URI

How to use

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

spanClassifier = RoBertaForQuestionAnswering.pretrained("roberta_qa_roberta_base_ca_cased_qa","ca") \
    .setInputCols(["document_question", "document_context"]) \
    .setOutputCol("answer") \
    .setCaseSensitive(True)

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

example = spark.createDataFrame([["What's my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")

result = pipeline.fit(example).transform(example)
val document = new MultiDocumentAssembler()
  .setInputCols("question", "context")
  .setOutputCols("document_question", "document_context")

val spanClassifier = RoBertaForQuestionAnswering
  .pretrained("roberta_qa_roberta_base_ca_cased_qa","ca")
  .setInputCols(Array("document_question", "document_context"))
  .setOutputCol("answer")
  .setCaseSensitive(true)
  .setMaxSentenceLength(512)

val pipeline = new Pipeline().setStages(Array(document, spanClassifier))

val example = Seq(
  ("Where was John Lenon born?", "John Lenon was born in London and lived in Paris. My name is Sarah and I live in London."),
  ("What's my name?", "My name is Clara and I live in Berkeley."))
  .toDF("question", "context")

val result = pipeline.fit(example).transform(example)
import nlu
nlu.load("ca.answer_question.roberta.base_cased").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")

Model Information

Model Name: roberta_qa_roberta_base_ca_cased_qa
Compatibility: Spark NLP 4.0.0+
License: Open Source
Edition: Official
Input Labels: [question, context]
Output Labels: [answer]
Language: ca
Size: 451.1 MB
Case sensitive: true
Max sentence length: 512

References

  • https://huggingface.co/projecte-aina/roberta-base-ca-cased-qa
  • https://arxiv.org/abs/1907.11692
  • https://github.com/projecte-aina/club