Overview
Fairseq is a sequence-to-sequence toolkit developed by Facebook AI Research (FAIR). Built on PyTorch, it enables researchers and developers to train custom models for a variety of NLP tasks, including machine translation, text summarization, language modeling, and other text generation applications. Fairseq supports convolutional neural networks (CNN), long short-term memory (LSTM) networks, and Transformer networks. It offers reference implementations of sequence modeling papers and features multi-GPU training capabilities across multiple machines. The toolkit provides tools for tasks such as back-translation, unsupervised quality estimation, and lexically constrained decoding, facilitating advanced research and development in sequence modeling.