fairseq: A Fast, Extensible Toolkit for Sequence Modeling
This toolkit provides a practical solution for researchers and developers working on text generation tasks, though it is incremental as it builds on existing PyTorch frameworks.
The authors introduced fairseq, an open-source toolkit for sequence modeling tasks like translation and summarization, which supports fast, extensible training and inference on GPUs.
fairseq is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text generation tasks. The toolkit is based on PyTorch and supports distributed training across multiple GPUs and machines. We also support fast mixed-precision training and inference on modern GPUs. A demo video can be found at https://www.youtube.com/watch?v=OtgDdWtHvto