readme: # InfoXLM
  
  **InfoXLM** (NAACL 2021, [paper](https://arxiv.org/pdf/2007.07834.pdf), [repo](https://github.com/microsoft/unilm/tree/master/infoxlm), [model](https://huggingface.co/microsoft/infoxlm-base)) InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training.
  
  **MD5**
  
  ```
  b9d214025837250ede2f69c9385f812c  config.json
  bd6b1f392293f0cd9cd829c02971ecd9  pytorch_model.bin
  bf25eb5120ad92ef5c7d8596b5dc4046  sentencepiece.bpe.model
  eedbd60a7268b9fc45981b849664f747  tokenizer.json
  ```
  
  **BibTeX**
  
  ```
  @inproceedings{chi-etal-2021-infoxlm,
    title = "{I}nfo{XLM}: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training",
    author={Chi, Zewen and Dong, Li and Wei, Furu and Yang, Nan and Singhal, Saksham and Wang, Wenhui and Song, Xia and Mao, Xian-Ling and Huang, Heyan and Zhou, Ming},
    booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.naacl-main.280",
    doi = "10.18653/v1/2021.naacl-main.280",
    pages = "3576--3588",}
  ```