facebookresearch/fairseq-lua
A Lua-based sequence-to-sequence neural machine translation toolkit implementing convolutional and LSTM encoder-decoder models.
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Fairseq is a sequence-to-sequence learning toolkit developed by Facebook AI Research for Neural Machine Translation. It implements convolutional NMT models as described in two academic papers along with standard LSTM-based models. The toolkit supports multi-GPU training on a single machine and provides fast beam search generation on both CPU and GPU. Pre-trained models are available for English-French, English-German, and English-Romanian translation. New development has moved to the PyTorch version (fairseq-py), and this Lua version is preserved without active support.
Frequently asked
- What is facebookresearch/fairseq-lua?
- A Lua-based sequence-to-sequence neural machine translation toolkit implementing convolutional and LSTM encoder-decoder models.
- Is fairseq-lua open source?
- Yes — facebookresearch/fairseq-lua is an open-source project tracked on heatdrop.
- What language is fairseq-lua written in?
- facebookresearch/fairseq-lua is primarily written in Lua.
- How popular is fairseq-lua?
- facebookresearch/fairseq-lua has 3.7k stars on GitHub.
- Where can I find fairseq-lua?
- facebookresearch/fairseq-lua is on GitHub at https://github.com/facebookresearch/fairseq-lua.