readme: ---
  language:
  - "zh"
  tags:
  - "chinese"
  - "token-classification"
  - "pos"
  - "wikipedia"
  - "dependency-parsing"
  datasets:
  - "universal_dependencies"
  license: "apache-2.0"
  pipeline_tag: "token-classification"
  ---
  
  # chinese-roberta-large-upos
  
  ## Model Description
  
  This is a BERT model pre-trained on Chinese Wikipedia texts (both simplified and traditional) for POS-tagging and dependency-parsing, derived from [chinese-roberta-wwm-ext-large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech).
  
  ## How to Use
  
  ```py
  from transformers import AutoTokenizer,AutoModelForTokenClassification
  tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/chinese-roberta-large-upos")
  model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/chinese-roberta-large-upos")
  ```
  
  or
  
  ```py
  import esupar
  nlp=esupar.load("KoichiYasuoka/chinese-roberta-large-upos")
  ```
  
  ## See Also
  
  [esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
  
  