Introduction fairseq is a popular open-source sequence-to-sequence learning library developed by Facebook AI Research. It provides a flexible and extensible framework for training and evaluating state-of-the-art models in natural language processing, including models for machine translation, text generation, and more. fairseq supports various advanced architectures and offers tools to streamline the process of developing and experimenting with cutting-edge machine learning models.

Features Advanced Models: Implements a wide range of state-of-the-art models for tasks such as machine translation, language modeling, and sequence generation. Flexible Framework: Designed to be highly modular, allowing users to customize and extend the library to meet specific research or application needs. Efficient Training: Includes support for efficient training and distributed training across multiple GPUs or nodes. Pre-trained Models: Provides access to a variety of pre-trained models that can be fine-tuned for specific tasks or directly used for inference. Extensive Documentation: Comprehensive guides and tutorials for getting started, using different models, and integrating the library into projects. Active Community: Supported by an active community of researchers and developers, with regular updates and contributions.