Catalan RobertaForQuestionAnswering Base Cased model (from projecte-aina)

Description

Pretrained RobertaForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. roberta-base-ca-v2-cased-qa is a Catalan model originally trained by projecte-aina.

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_base_ca_v2_cased","ca")\
     .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_base_ca_v2_cased","ca")
     .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("ca.answer_question.roberta.cased_v2_base").predict("""What's my name?|||"My name is Clara and I live in Berkeley.""")

Model Information

References

• https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-qa
• https://arxiv.org/abs/1907.11692
• https://github.com/projecte-aina/club
• https://www.apache.org/licenses/LICENSE-2.0
• https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca%7Cen
• https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina
• https://paperswithcode.com/sota?task=question-answering&dataset=CatalanQA