FAIRSEQ: A Fast, Extensible Toolkit for Sequence Modeling

North American Chapter of the Association for Computational Linguistics (NAACL)


FAIRSEQ is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text generation tasks. The toolkit is based on PyTorch and supports distributed training across multiple GPUs and machines. We also support fast mixed-precision training and inference on modern GPUs. A demo video can be found here: https://www.youtube.com/watch?v=OtgDdWtHvto.

Latest Publications

Log-structured Protocols in Delos

Mahesh Balakrishnan, Mihir Dharamshi, David Geraghty, Santosh Ghosh, Filip Gruszczynski, Jun Li, Jingming Liu, Suyog Mapara, Rajeev Nagar, Ivailo Nedelchev, Francois Richard, Chen Shen, Yee Jiun Song, Rounak Tibrewal, Vidhya Venkat, Ahmed Yossef, Ali Zaveri