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Update README.md

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@@ -46,7 +46,7 @@ Our fine-tuned BERT model is this repository. Our Package also supports download
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  from qa_metrics.transformerMatcher import TransformerMatcher
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  question = "who will take the throne after the queen dies"
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- tm = TransformerMatcher("distilbert")
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  scores = tm.get_scores(reference_answer, candidate_answer, question)
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  match_result = tm.transformer_match(reference_answer, candidate_answer, question)
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  print("Score: %s; CF Match: %s" % (scores, match_result))
 
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  from qa_metrics.transformerMatcher import TransformerMatcher
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  question = "who will take the throne after the queen dies"
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+ tm = TransformerMatcher("roberta")
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  scores = tm.get_scores(reference_answer, candidate_answer, question)
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  match_result = tm.transformer_match(reference_answer, candidate_answer, question)
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  print("Score: %s; CF Match: %s" % (scores, match_result))