rStar-Math from Microsoft enhances models like Qwen-7B and Phi3-mini, enabling them to tackle math problems at OpenAI o1 levels. Key features include step-by-step reasoning, automated code verification, and self-learning through iterative training. With 747,000 math problems used for training, accuracy soared—Qwen2.5-Math-7B reached 90%, and Phi3-mini-3.8B hit 86.4%. Check it out on GitHub

Fascinating to see Microsoft's rStar-Math enhance AI models' math problem-solving capabilities. Automated code verification and self-learning through iterative training are game-changers. Impressive accuracy results, especially Qwen2.5-Math-7B's 90%!