Spanish RobertaForQuestionAnswering Base Cased model (from mrm8488)

Description

Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. longformer-base-4096-spanish-finetuned-squad is a Spanish model originally trained by mrm8488.

Live Demo Open in Colab Download Copy S3 URI

How to use

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

Question_Answering = RoBertaForQuestionAnswering.pretrained("roberta_qa_longformer_base_4096_spanish_finetuned_squad","es")\
     .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 = RoBertaForQuestionAnswering.pretrained("roberta_qa_longformer_base_4096_spanish_finetuned_squad","es")
     .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)

import nlu
nlu.load("es.answer_question.squad.roberta.base_4096.by_mrm8488").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")

Model Information

References

• https://huggingface.co/mrm8488/longformer-base-4096-spanish-finetuned-squad
• https://es.wikipedia.org/
• https://creativecommons.org/licenses/by-sa/3.0/legalcode
• https://es.wikinews.org/
• https://creativecommons.org/licenses/by/2.5/
• http://clic.ub.edu/corpus/en
• https://creativecommons.org/licenses/by/4.0/legalcode
• https://twitter.com/mrm8488
• https://www.narrativa.com/