fairseq
Fairseq is an open-source toolkit for sequence modeling developed by Facebook AI Research (FAIR). It provides reference implementations for training and evaluating neural sequence-to-sequence models, with an emphasis on translation, language modeling, and speech tasks. Built on PyTorch, fairseq offers modular components for data processing, model architectures, and training loops, enabling researchers to implement and experiment with new ideas efficiently.
Core features include a suite of model architectures such as Transformer-based encoders and decoders, convolutional seq2seq
Fairseq is released under the MIT license and maintained by FAIR with community contributions. It is designed