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SeRL: Self-Play Reinforcement Learning for Large Language Models with Limited Data
The main features of wantbook-book/serl are: Single Agent Optimization, Unsupervised Reward Methods.
Projects with overlapping indexed features include: chengsong-huang/r-zero — Check out our paper or webpage for the details. wangqinsi1/vision-zero — A domain-agnostic framework enabling VLM self-improvement through competitive visual games. hkust-nlp/mstar — :star: Project Page . gpoesia/minimo — This is the implementation of the following paper:. ezelikman/star — 1. STaR 2. Mesh Transformer JAX 1. Updates 3. Pretrained Models 1. GPT-J-6B 1. Links 2. Acknowledgments 3. License 4.… chengpengli1003/cort.
A domain-agnostic framework enabling VLM self-improvement through competitive visual games
1. STaR 2. Mesh Transformer JAX 1. Updates 3. Pretrained Models 1. GPT-J-6B 1. Links 2. Acknowledgments 3. License 4. Model Details 5. Zero-Shot Evaluations 4. Architecture and Usage 1. Fine-tuning 2. JAX Dependency 5. TODO
