初始化项目，由ModelHub XC社区提供模型

Model: TIGER-Lab/General-Reasoner-Qwen2.5-7B
Source: Original Platform

README.md

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+---
+license: apache-2.0
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-7B
+tags:
+- General-Reasoner-7B
+---
+
+
+# General-Reasoner: Advancing LLM Reasoning Across All Domains
+
+<p align="center">
+  <a href="https://github.com/TIGER-AI-Lab/General-Reasoner" target="_blank">💻 Code</a> |
+  <a href="https://arxiv.org/abs/2505.14652" target="_blank">📄 Paper</a> |
+  <a href="https://huggingface.co/datasets/TIGER-Lab/WebInstruct-verified" target="_blank">📊 Dataset</a> |
+  <a href="https://huggingface.co/collections/TIGER-Lab/general-reasoner-67fe9386e43e046489eac013" target="_blank">🤗 Model</a> |
+  <a href="https://tiger-ai-lab.github.io/General-Reasoner/" target="_blank">🌐 Project Page</a>
+</p>
+
+
+
+## Overview
+
+<p align="center">
+  <img src="https://tiger-ai-lab.github.io/General-Reasoner/static/images/teaser.png" alt="General-Reasoner Teaser" width="650"/>
+</p>
+<p align="center" style="font-style: italic; font-size: 0.95rem;">
+  <em>
+    Figure: Effectiveness of <strong>General-Reasoner</strong> trained with diverse verifiable reasoning questions using model-based verifier compared to baseline methods on various reasoning tasks.
+  </em>
+</p>
+
+**General-Reasoner** is a training paradigm for large language models (LLMs), designed to robustly enhance reasoning abilities across diverse domains—not just mathematics and coding, but also physics, chemistry, finance, humanities, and more.
+
+**Key features:**
+- **Zero RL Training:** Direct reinforcement learning from base LLMs, bypassing intermediate supervised stages.
+- **Diverse Reasoning Data:** 230K+ high-quality, verifiable questions sourced from the web and filtered for answer verifiability across disciplines.
+- **Model-Based Verifier:** Compact 1.5B generative verifier model for context-aware, chain-of-thought answer validation, outperforming traditional rule-based methods.
+
+**This specific model is the General-Reasoner variant trained based on [Qwen2.5-7B-Base](https://huggingface.co/Qwen/Qwen2.5-7B).**
+
+
+## Main Results
+General-Reasoner outperforms base and supervised models on a variety of reasoning benchmarks, demonstrating robust generalization across domains:
+
+<p align="center">
+  <a href="https://github.com/TIGER-AI-Lab/General-Reasoner/raw/refs/heads/gh-pages/static/images/results_general.png" target="_blank">
+    <img src="https://github.com/TIGER-AI-Lab/General-Reasoner/raw/refs/heads/gh-pages/static/images/results_general.png" alt="Main Results" width="600">
+  </a>
+</p>
+
+## Citation
+
+If you feel our work is helpful, please cite:
+
+```bibtex
+@article{general-reasoner,
+  title={{G}eneral-{R}easoner: Advancing LLM Reasoning Across All Domains},
+  author={Xueguang Ma and Qian Liu and Dongfu Jiang and Ge Zhang and Zejun Ma and Wenhu Chen},
+  year={2025},
+  journal={arXiv:2505.14652},
+  url={https://arxiv.org/abs/2505.14652}
+}
+```