readme: ---
  language:
    - zh
  thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
  tags:
    - pytorch
    - token-classification
    - bert
    - zh
  license: gpl-3.0
  ---
  
  # CKIP BERT Base Han Chinese POS
  
  This model provides part-of-speech (POS) tagging for the ancient Chinese language. Our training dataset covers four eras of the Chinese language.
  
  ## Homepage
  * [ckiplab/han-transformers](https://github.com/ckiplab/han-transformers)
  
  ## Training Datasets
  The copyright of the datasets belongs to the Institute of Linguistics, Academia Sinica.
  * [中央研究院上古漢語標記語料庫](http://lingcorpus.iis.sinica.edu.tw/cgi-bin/kiwi/akiwi/kiwi.sh)
  * [中央研究院中古漢語語料庫](http://lingcorpus.iis.sinica.edu.tw/cgi-bin/kiwi/dkiwi/kiwi.sh)
  * [中央研究院近代漢語語料庫](http://lingcorpus.iis.sinica.edu.tw/cgi-bin/kiwi/pkiwi/kiwi.sh)
  * [中央研究院現代漢語語料庫](http://asbc.iis.sinica.edu.tw)
  
  ## Contributors
  * Chin-Tung Lin at [CKIP](https://ckip.iis.sinica.edu.tw/)
  
  ## Usage
  
  * Using our model in your script
      ```python
      from transformers import (
        AutoTokenizer,
        AutoModel,
      )
  
      tokenizer = AutoTokenizer.from_pretrained("ckiplab/bert-base-han-chinese-pos")
      model = AutoModel.from_pretrained("ckiplab/bert-base-han-chinese-pos")
      ```
  
  * Using our model for inference
      ```python
      >>> from transformers import pipeline
      >>> classifier = pipeline("token-classification", model="ckiplab/bert-base-han-chinese-pos")
      >>> classifier("帝堯曰放勳")
  
      [{'entity': 'NB1',
        'score': 0.99410427,
        'index': 1,
        'word': '帝',
        'start': 0,
        'end': 1},
       {'entity': 'NB1',
        'score': 0.98874336,
        'index': 2,
        'word': '堯',
        'start': 1,
        'end': 2},
       {'entity': 'VG',
        'score': 0.97059363,
        'index': 3,
        'word': '曰',
        'start': 2,
        'end': 3},
       {'entity': 'NB1',
        'score': 0.9864504,
        'index': 4,
        'word': '放',
        'start': 3,
        'end': 4},
       {'entity': 'NB1',
        'score': 0.9543974,
        'index': 5,
        'word': '勳',
        'start': 4,
        'end': 5}]
      ```
  
  