metadata
language:
- zh
thumbnail: https://ckip.iis.sinica.edu.tw/files/ckip_logo.png
tags:
- pytorch
- lm-head
- bert
- zh
license: gpl-3.0
CKIP BERT Base Han Chinese
Pretrained model on Ancient Chinese language using a masked language modeling (MLM) objective.
Homepage
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'}]