This repository implements the training framework from MetaAI’s Self-Rewarding Language Model paper. It enables language models to iteratively improve themselves by serving as their own reward models during training. The framework incorporates Direct Preference Optimization (DPO) for preference-based training and also includes an implementation of the SPIN training method. Built on PyTorch with integration for transformer architectures.