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dependency-parsing

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  1. README.md +13 -1
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@@ -17,7 +17,7 @@ widget:
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  ## Model Description
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- This is a GPT-2 model for POS-tagging, derived from [gpt2-large-japanese-char](https://huggingface.co/ku-nlp/gpt2-large-japanese-char). Every short-unit-word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech) and [FEATS](https://universaldependencies.org/u/feat/).
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  ## How to Use
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  print(nlp("国境の長いトンネルを抜けると雪国であった。"))
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  ```
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  ## Model Description
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+ This is a GPT-2 model for POS-tagging and dependency-parsing, derived from [gpt2-large-japanese-char](https://huggingface.co/ku-nlp/gpt2-large-japanese-char). Every short-unit-word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech) and [FEATS](https://universaldependencies.org/u/feat/).
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  ## How to Use
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  print(nlp("国境の長いトンネルを抜けると雪国であった。"))
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  ```
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+ or
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+
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+ ```py
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+ import esupar
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+ nlp=esupar.load("KoichiYasuoka/gpt2-large-japanese-upos")
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+ print(nlp("国境の長いトンネルを抜けると雪国であった。"))
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+ ```
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+
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+ ## See Also
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+
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+ [esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
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+