Fairseq is an open-source sequence modeling toolkit developed by Facebook AI Research. It enables researchers and developers to train custom models for various tasks, including translation, summarization, language modeling, and other text generation tasks. Built on PyTorch, Fairseq supports distributed training across multiple GPUs and machines and offers fast mixed-precision training and inference on modern GPUs
Key Features
modeling, and other text generation tasks.
Reference implementations of various sequence-to-sequence models, including Transformer, BART, and Convolutional Neural Networks (CNN).
Optimized for fast mixed-precision training and inference on modern GPUs.
Extensible architecture allowing for easy integration of new models and tasks.
Tools for preprocessing, training, and evaluation of sequence models.
Support for distributed training across multiple GPUs and machines
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