Joint Laboratory of HIT and iFLYTEK Research (HFL)
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README.md
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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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# This model is trained on 180G data, we recommend using this one than the original version.
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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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```
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