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  This model is used to tag the tokens in an input sequence with information about the different signs of syntactic complexity that they contain. For more details, please see Chapters 2 and 3 of my thesis (https://rj3vans.github.io/Evans2020_SentenceSimplificationForTextProcessing.pdf.
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  It was derived using code written by Dr. Le An Ha at the University of Wolverhampton.
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  print([(token, label_list[prediction]) for token, prediction in zip(tokens, predictions[0].tolist())])
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  ~~~
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- ======================================================================
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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ metrics:
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+ - accuracy
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+ base_model:
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+ - google-bert/bert-large-cased
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+ pipeline_tag: token-classification
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+ tags:
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+ - code
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+ ---
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  This model is used to tag the tokens in an input sequence with information about the different signs of syntactic complexity that they contain. For more details, please see Chapters 2 and 3 of my thesis (https://rj3vans.github.io/Evans2020_SentenceSimplificationForTextProcessing.pdf.
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  It was derived using code written by Dr. Le An Ha at the University of Wolverhampton.
 
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  print([(token, label_list[prediction]) for token, prediction in zip(tokens, predictions[0].tolist())])
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  ~~~
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+ ======================================================================