Search-R1's Core Technology Principles
Search-R1 is a GitHub open source project developed by PeterGriffinJin, whose core technical architecture is built on the veRL framework. The project uses reinforcement learning (RL) as the core training method , significantly improving the autonomous search and reasoning capabilities of large language models (LLM). The project supports the current mainstream open source models Qwen2.5-3B and Llama3.2-3B, and realizes a technological breakthrough by extending DeepSeek-R1 and TinyZero methods.
- Innovative application of RL techniques to LLM search capability training
- Complex training scenarios supporting multi-round task processing
- Complete code, datasets, and experimental logs available
The system has been publicly released in a technical paper (March 2025) and all models and data resources are available through the Hugging Face platform, providing a complete solution for researchers and developers.
This answer comes from the articleSearch-R1: A Tool for Reinforcement Learning to Train Large Models for Search and ReasoningThe
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