/CyBERTron-LM

CyBERTron-LM is a project which collects some pre-trained Transformer-based models.

Primary LanguagePythonMIT LicenseMIT

CyBERTron-LM

CyBERTron-LM is a research project on NLP. It collects some Models for solving NLP tasks (e.g., pre-training, understanding, generation or etc).

The current work in CyBERTron-LM include:

Reference

If you find this project useful in your work, you can cite the following papers if there's a need:

  • [1] Transcormer: Transformer for Sentence Scoring with Sliding Language Modeling, Kaitao Song, Yichong Leng, Xu Tan, Yicheng Zou, Tao Qin, Dongsheng Li, NeurIPS 2022.
  • [2] DiffusionNER: Boundary Diffusion for Named Entity Recognition, Yongliang Shen, Kaitao Song, Xu Tan, Dongsheng Li, Weiming Lu, Yueting Zhuang, ACL 2023.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.