| # longformer-base-4096 | |
| [Longformer](https://arxiv.org/abs/2004.05150) is a transformer model for long documents. | |
| `longformer-base-4096` is a BERT-like model started from the RoBERTa checkpoint and pretrained for MLM on long documents. It supports sequences of length up to 4,096. | |
| Longformer uses a combination of a sliding window (local) attention and global attention. Global attention is user-configured based on the task to allow the model to learn task-specific representations. | |
| Please refer to the examples in `modeling_longformer.py` and the paper for more details on how to set global attention. | |
| ### Citing | |
| If you use `Longformer` in your research, please cite [Longformer: The Long-Document Transformer](https://arxiv.org/abs/2004.05150). | |
| ``` | |
| @article{Beltagy2020Longformer, | |
| title={Longformer: The Long-Document Transformer}, | |
| author={Iz Beltagy and Matthew E. Peters and Arman Cohan}, | |
| journal={arXiv:2004.05150}, | |
| year={2020}, | |
| } | |
| ``` | |
| `Longformer` is an open-source project developed by [the Allen Institute for Artificial Intelligence (AI2)](http://www.allenai.org). | |
| AI2 is a non-profit institute with the mission to contribute to humanity through high-impact AI research and engineering. | |