rlm

rlm is an open-source reinforcement learning library designed for training and fine-tuning language models. It provides researchers and developers with utilities and abstractions to apply RL algorithms to LLMs, enabling reward-based optimization workflows. The project is hosted on GitHub and targets the ML research and AI development community.

• Reinforcement Learning for LLMs: Apply RL-based training loops and reward signals directly to language model fine-tuning pipelines.
• Open Source: Freely available on GitHub under an open-source license, allowing community contributions and modifications.
• Research-Oriented Tooling: Designed for ML researchers exploring RLHF and related techniques for language model alignment and optimization.
• Python-Based: Built in Python, making it easy to integrate with existing ML frameworks and LLM training stacks.
• Lightweight Abstractions: Provides modular components that can be composed into custom RL training workflows without heavy dependencies.