readme: ---
  language:
  - "ja"
  tags:
  - "japanese"
  - "token-classification"
  - "pos"
  - "dependency-parsing"
  datasets:
  - "universal_dependencies"
  license: "cc-by-sa-4.0"
  pipeline_tag: "token-classification"
  widget:
  - text: "国境の長いトンネルを抜けると雪国であった。"
  ---
  
  # deberta-small-japanese-upos
  
  ## Model Description
  
  This is a DeBERTa(V2) model pre-trained on 青空文庫 texts for POS-tagging and dependency-parsing, derived from [deberta-small-japanese-aozora](https://huggingface.co/KoichiYasuoka/deberta-small-japanese-aozora). Every short-unit-word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
  
  ## How to Use
  
  ```py
  import torch
  from transformers import AutoTokenizer,AutoModelForTokenClassification
  tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/deberta-small-japanese-upos")
  model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/deberta-small-japanese-upos")
  s="国境の長いトンネルを抜けると雪国であった。"
  t=tokenizer.tokenize(s)
  p=[model.config.id2label[q] for q in torch.argmax(model(tokenizer.encode(s,return_tensors="pt"))["logits"],dim=2)[0].tolist()[1:-1]]
  print(list(zip(t,p)))
  ```
  
  or
  
  ```py
  import esupar
  nlp=esupar.load("KoichiYasuoka/deberta-small-japanese-upos")
  print(nlp("国境の長いトンネルを抜けると雪国であった。"))
  ```
  
  ## See Also
  
  [esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
  
  