slime

Overview

slime, by THUDM, is a newly highlighted post-training framework that focuses on reinforcement-learning-style scaling for large language models. It provides tooling for reward modeling, policy optimization, and evaluation, designed to sit on top of existing pretrained LLMs. Developers and researchers should care because it offers a modern, open-source stack for RL post-training that can be integrated into custom pipelines, enabling more controllable LLM behavior without rebuilding training infrastructure from scratch.