TinyZero: Unlocking Reasoning in LLMs on a Budget
2025-01-25
TinyZero is a project demonstrating how to imbue large language models (LLMs) with self-verification and search capabilities at low cost, using reinforcement learning. Built upon veRL and experimenting with the Qwen2.5 series, TinyZero provides detailed instructions for installation, data preparation, and training. Even smaller models can achieve sophisticated reasoning. The project showcases the feasibility of enhancing LLMs via RL, offering a new approach to cost-effective AI research.
AI
Low-cost AI