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--- |
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language: |
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- zh |
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license: "apache-2.0" |
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--- |
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## Chinese ELECTRA |
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Google and Stanford University released a new pre-trained model called ELECTRA, which has a much compact model size and relatively competitive performance compared to BERT and its variants. |
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For further accelerating the research of the Chinese pre-trained model, the Joint Laboratory of HIT and iFLYTEK Research (HFL) has released the Chinese ELECTRA models based on the official code of ELECTRA. |
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ELECTRA-small could reach similar or even higher scores on several NLP tasks with only 1/10 parameters compared to BERT and its variants. |
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This project is based on the official code of ELECTRA: [https://github.com/google-research/electra](https://github.com/google-research/electra) |
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You may also interested in, |
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- Chinese BERT series: https://github.com/ymcui/Chinese-BERT-wwm |
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- Chinese ELECTRA: https://github.com/ymcui/Chinese-ELECTRA |
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- Chinese XLNet: https://github.com/ymcui/Chinese-XLNet |
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- Knowledge Distillation Toolkit - TextBrewer: https://github.com/airaria/TextBrewer |
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More resources by HFL: https://github.com/ymcui/HFL-Anthology |
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## Citation |
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If you find our resource or paper is useful, please consider including the following citation in your paper. |
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- https://arxiv.org/abs/2004.13922 |
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``` |
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@inproceedings{cui-etal-2020-revisiting, |
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title = "Revisiting Pre-Trained Models for {C}hinese Natural Language Processing", |
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author = "Cui, Yiming and |
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Che, Wanxiang and |
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Liu, Ting and |
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Qin, Bing and |
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Wang, Shijin and |
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Hu, Guoping", |
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booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings", |
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month = nov, |
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year = "2020", |
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address = "Online", |
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publisher = "Association for Computational Linguistics", |
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url = "https://www.aclweb.org/anthology/2020.findings-emnlp.58", |
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pages = "657--668", |
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} |
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``` |
