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Open-R1: an open reproduction of DeepSeek-R1
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
These questions prompted us to launch the Open-R1 project, an initiative to systematically reconstruct DeepSeek-R1’s data and training pipeline, validate its claims, and push the boundaries of open reasoning models. By building Open-R1, we aim to provide transparency on how reinforcement learning can enhance reasoning, share reproducible insights with the open-source community, and create a foundation for future models to leverage these techniques. From there, it went through more RL and refinement steps, including rejecting low-quality outputs with both human preference based and verifiable reward, to create a model that not only reasons well but also produces polished and consistent answers.
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