fairseq
The toolkit that trained a decade of breakthroughs
Latest: fairseq-py (actively archived-era; final major line 0.12.x)
FAIR's sequence-to-sequence research toolkit, open-sourced in 2017 — the workbench on which a decade of Meta breakthroughs was built: convolutional seq2seq, RoBERTa, BART, XLM-R, wav2vec 2.0, NLLB, and MMS all shipped as fairseq examples. One of the most influential NLP codebases ever released.
Why it matters
fairseq was the workbench for a decade of Meta NLP: RoBERTa, BART, XLM-R, wav2vec 2.0, NLLB and MMS all shipped as fairseq examples, and its 32,000-star codebase trained much of the field's translation and speech research. The repository is now archived, but its examples directory remains a museum of modern NLP.
Facts
- ~32,200 GitHub stars.
- Began as Lua Torch code for convolutional translation (pre-Transformer, May 2017) before the PyTorch rewrite.
- Its examples directory reads like a museum of modern NLP.
Try it yourself
pip install fairseq ↗ Archived repo on GitHub ↗ Read the paper ↗