KoichiYasuoka
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dependency-parsing
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README.md
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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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```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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## See Also
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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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