readme: ---
  license: apache-2.0
  ---
  
  Pretrained models for our paper (https://arxiv.org/abs/2210.08431)
  ```bibtex
  @inproceedings{wu-etal-2022-modeling,
      title = "Modeling Context With Linear Attention for Scalable Document-Level Translation",
      author = "Zhaofeng Wu and Hao Peng and Nikolaos Pappas and Noah A. Smith",
      booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
      month = dec,
      year = "2022",
      publisher = "Association for Computational Linguistics",
  }
  ```
  
  Please see the "Files and versions" tab for the models. You can find our IWSLT models and our OpenSubtitles models that are early-stopped based on BLEU and consistency scores, respectively. The `c` part in the checkpoint name refers to the number of context sentences used; it is the same as the sliding window size (the `L` in our paper) minus one.
  