QwQ-32B: Embracing the Power of Reinforcement Learning

GitHub Pages · 1 year ago · 43

Qwen released QwQ-32B, a 32 billion parameter language model that applies reinforcement learning techniques to improve reasoning capabilities beyond standard pretraining methods. The model follows approaches demonstrated by DeepSeek R1, which used multi-stage training and cold-start data to achieve enhanced performance on reasoning tasks. The release aims to advance research into scaling reinforcement learning as a method for improving language model reasoning and intelligence.