初始化项目，由ModelHub XC社区提供模型

Model: youngzhong/SOD-GRPO_teacher-4B
Source: Original Platform

README.md

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+---
+language:
+- en
+license: apache-2.0
+library_name: transformers
+base_model: Qwen/Qwen3-4B
+tags:
+- agent
+- tool-use
+- reinforcement-learning
+- GRPO
+- math
+- code
+- reasoning
+pipeline_tag: text-generation
+---
+
+<div align="center">
+
+<h1>SOD-GRPO_teacher-4B</h1>
+
+<p>
+  <a href="https://arxiv.org/abs/2605.07725">
+    <img src="https://img.shields.io/badge/Paper-arXiv-red?logo=arxiv&logoColor=red" alt="Paper on arXiv"/>
+  </a>
+  <a href="https://github.com/YoungZ365/SOD">
+    <img src="https://img.shields.io/badge/Code-GitHub-black?logo=github&logoColor=white" alt="Code on GitHub"/>
+  </a>
+  <a href="https://huggingface.co/collections/youngzhong/sod-6a03530369d76913c24a4ffb">
+    <img src="https://img.shields.io/badge/Collection-SOD-yellow?logo=huggingface" alt="HuggingFace Collection"/>
+  </a>
+  <a href="https://huggingface.co/papers/2605.07725">
+    <img src="https://img.shields.io/badge/Daily%20Paper-SOD-yellow?logo=huggingface&logoColor=yellow" alt="HuggingFace Daily Paper"/>
+  </a>
+  <a href="https://www.alphaxiv.org/abs/2605.07725">
+    <img src="https://img.shields.io/badge/alphaXiv-2605.07725-purple?logo=arxiv&logoColor=white" alt="alphaXiv"/>
+  </a>
+</p>
+
+</div>
+
+## About
+
+**SOD-GRPO_teacher-4B** is a 4B agentic reasoning model trained with **GRPO (Group Relative Policy Optimization)**, serving as the teacher model in the SOD distillation framework.
+
+This model is used to distill smaller student models ([SOD-0.6B](https://huggingface.co/youngzhong/SOD-0.6B) and [SOD-1.7B](https://huggingface.co/youngzhong/SOD-1.7B)) via the SOD method, which introduces adaptive step-level weighting to handle cascading error propagation in tool-integrated reasoning.
+
+## Model Information
+
+| Attribute | Value |
+|-----------|-------|
+| Base Model | [Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) |
+| Training Pipeline | Cold-Start SFT → GRPO |
+| Parameters | 4B |
+
+## Related Models
+
+| Model | Description |
+|-------|-------------|
+| [SOD-0.6B](https://huggingface.co/youngzhong/SOD-0.6B) | SOD-distilled 0.6B student |
+| [SOD-1.7B](https://huggingface.co/youngzhong/SOD-1.7B) | SOD-distilled 1.7B student |
+| [SOD-GRPO_teacher-4B](https://huggingface.co/youngzhong/SOD-GRPO_teacher-4B) | GRPO-trained 4B teacher model (this model) |
+
+## Performance
+
+We report **average@32** over 5 runs on challenging math, science, and code benchmarks.
+
+| Method | AIME 2024 | AIME 2025 | GPQA-Diamond | LiveCodeBench-v6 | Average |
+|--------|-----------|-----------|--------------|------------------|---------|
+| **GRPO (This Model)** | **67.60** | **60.42** | **55.19** | **63.13** | **61.59** |
+
+### Distilled Students
+
+| Model | AIME 2024 | AIME 2025 | GPQA-Diamond | LiveCodeBench-v6 | Average |
+|-------|-----------|-----------|--------------|------------------|---------|
+| SOD-0.6B | 20.84 | 26.13 | 22.19 | 27.72 | 24.22 |
+| SOD-1.7B | 50.83 | 41.72 | 38.72 | 40.63 | 42.98 |
+
+## Acknowledgement
+
+We sincerely thank the authors of [DemyAgent-4B](https://huggingface.co/Gen-Verse/DemyAgent-4B) and the paper *"Demystifying Reinforcement Learning in Agentic Reasoning"* ([arXiv:2510.11701](https://arxiv.org/abs/2510.11701)) for their contribution.
+
+## Citation
+
+```bibtex
+@article{zhong2026sod,
+  title={SOD: Step-wise On-policy Distillation for Small Language Model Agents},
+  author={Zhong, Qiyong and Zheng, Mao and Song, Mingyang and Lin, Xin and Sun, Jie and Jiang, Houcheng and Wang, Xiang and Fang, Junfeng},
+  journal={arXiv preprint arXiv:2605.07725},
+  year={2026}
+}
+```