fairseq2 is a research-focused sequence modeling library that provides modular APIs for training custom models on content generation tasks including language modeling, speech translation, and multilingual speech recognition. It is a reboot of the original fairseq with a clean architecture and supports recent FAIR research on Large Concept Models, Seamless speech translation, and diverse preference optimization.