Rbt6

🚀 重新訓練的6層RoBERTa-wwm-ext模型

本項目提供了一個重新訓練的6層RoBERTa-wwm-ext模型，旨在進一步加速中文自然語言處理任務，為相關領域的研究和應用提供有力支持。

🚀 快速開始

本倉庫基於 https://github.com/google-research/bert 開發。你還可能對以下項目感興趣：

• 中文BERT系列: https://github.com/ymcui/Chinese-BERT-wwm
• 中文MacBERT: https://github.com/ymcui/MacBERT
• 中文ELECTRA: https://github.com/ymcui/Chinese-ELECTRA
• 中文XLNet: https://github.com/ymcui/Chinese-XLNet
• 知識蒸餾工具包 - TextBrewer: https://github.com/airaria/TextBrewer

更多由HFL提供的資源請見：https://github.com/ymcui/HFL-Anthology

✨ 主要特性

為了進一步加速中文自然語言處理，我們提供了基於全詞掩碼的中文預訓練BERT模型。

論文：Pre-Training with Whole Word Masking for Chinese BERT
作者：Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Ziqing Yang, Shijin Wang, Guoping Hu

📄 許可證

本項目採用 apache-2.0 許可證。

📚 詳細文檔

引用

如果你發現本技術報告或資源有用，請在你的論文中引用以下技術報告：

• 主要引用：https://arxiv.org/abs/2004.13922

@inproceedings{cui-etal-2020-revisiting,
    title = "Revisiting Pre-Trained Models for {C}hinese Natural Language Processing",
    author = "Cui, Yiming  and
      Che, Wanxiang  and
      Liu, Ting  and
      Qin, Bing  and
      Wang, Shijin  and
      Hu, Guoping",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.findings-emnlp.58",
    pages = "657--668",
}

• 次要引用：https://arxiv.org/abs/1906.08101

@article{chinese-bert-wwm,
  title={Pre-Training with Whole Word Masking for Chinese BERT},
  author={Cui, Yiming and Che, Wanxiang and Liu, Ting and Qin, Bing and Yang, Ziqing and Wang, Shijin and Hu, Guoping},
  journal={arXiv preprint arXiv:1906.08101},
  year={2019}
 }