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CKIP BERT Base Han Chinese

Pretrained model on Ancient Chinese language using a masked language modeling (MLM) objective.

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Training Datasets

The copyright of the datasets belongs to the Institute of Linguistics, Academia Sinica.

Contributors

  • Chin-Tung Lin at CKIP

Usage

  • Using our model in your script

    from transformers import (
      AutoTokenizer,
      AutoModel,
    )
    
    tokenizer = AutoTokenizer.from_pretrained("ckiplab/bert-base-han-chinese")
    model = AutoModel.from_pretrained("ckiplab/bert-base-han-chinese")
    
  • Using our model for inference

    >>> from transformers import pipeline
    >>> unmasker = pipeline('fill-mask', model='ckiplab/bert-base-han-chinese')
    >>> unmasker("黎[MASK]於變時雍。")
    
    [{'sequence': '黎 民 於 變 時 雍 。',
    'score': 0.14885780215263367,
    'token': 3696,
    'token_str': '民'},
    {'sequence': '黎 庶 於 變 時 雍 。',
    'score': 0.0859643816947937,
    'token': 2433,
    'token_str': '庶'},
    {'sequence': '黎 氏 於 變 時 雍 。',
    'score': 0.027848130092024803,
    'token': 3694,
    'token_str': '氏'},
    {'sequence': '黎 人 於 變 時 雍 。',
    'score': 0.023678112775087357,
    'token': 782,
    'token_str': '人'},
    {'sequence': '黎 生 於 變 時 雍 。',
    'score': 0.018718384206295013,
    'token': 4495,
    'token_str': '生'}]
    
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