🚀 A curated collection of training recipes for RLite 📜✨, designed to provide comprehensive guidance on implementing reinforcement learning (RL) techniques for large language models (LLMs) and vision-language models (VLMs). This repository offers modular configurations ⚙️, training workflows 📊, and best practices 🌟 to help users reproduce state-of-the-art RL-driven results 🏆 in alignment, fine-tuning, and optimization tasks.
🌱 While not exhaustive, the current recipes focus on foundational and emerging methodologies, serving as a starting point for adapting RLite to custom projects. Contributions are welcome 🙌 to expand coverage of existing research and benchmarks.
🚧 Under active development — we aim to expand support collaboratively while maintaining reproducibility 🔍✅ and clarity ✨📖. New recipes will be added progressively as the ecosystem evolves!
"Cooking up RL innovations, one recipe at a time!" 👩🍳🔥
Developer's guide.
We use pre-commit and git cz to sanitize the commits. You can run pre-commit before git cz to avoid repeatedly input the commit messages.
pip install pre-commit
# Install pre-commit hooks
pre-commit install
pre-commit install --hook-type commit-msg
# Install this emoji-style tool
sudo npm install -g git-cz --no-audit --verbose --registry=https://registry.npmmirror.com
# Install rlite and development dependencies
pip install -e ".[dev]"- Single line code length is 99 characters, comments and documents are 79 characters.
- Write unit tests for atomic capabilities to ensure that
pytestdoes not throw an error.
Run pre-commit to automatically lint the code:
pre-commit run --all-files