torchtune

torchtune: PyTorch Native Post-Training Library for LLMs

Meta's PyTorch team introduces torchtune, a PyTorch-native library for post-training LLMs that emphasizes modularity, hackability, and direct access to underlying PyTorch components. The library supports fine-tuning, experimentation, and deployment-oriented workflows across distributed training settings. Benchmarked against popular frameworks Axolotl and Unsloth, torchtune demonstrates competitive performance and memory efficiency while maintaining flexibility for research iteration. The paper presents design principles, model builders, training recipes, and distributed training stack details.