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+ # Chinese BART-Large
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+
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+ ## Model description
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+
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+ This is an implementation of Chinese BART-Large.
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+
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+ ## Usage
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+
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+ ```python
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+ >>> from transformers import BertTokenizer, BartForConditionalGeneration, Text2TextGenerationPipeline
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+ >>> tokenizer = BertTokenizer.from_pretrained("fnlp/bart-large-chinese")
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+ >>> model = BartForConditionalGeneration.from_pretrained("fnlp/bart-large-chinese")
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+ >>> text2text_generator = Text2TextGenerationPipeline(model, tokenizer)
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+ >>> text2text_generator("北京是[MASK]的首都", max_length=50, do_sample=False)
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+ [{'generated_text': '北 京 是 中 华 人 民 共 和 国 的 首 都'}]
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+ ```
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+
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+ **Note: Please use BertTokenizer for the model vocabulary. DO NOT use original BartTokenizer.**
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @article{shao2021cpt,
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+ title={CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation},
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+ author={Yunfan Shao and Zhichao Geng and Yitao Liu and Junqi Dai and Fei Yang and Li Zhe and Hujun Bao and Xipeng Qiu},
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+ journal={arXiv preprint arXiv:2109.05729},
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+ year={2021}
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+ }
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+ ```
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+