Update model card: add pipeline tag, paper link, and sample usage

README.md

@@ -1,11 +1,13 @@
 ---
-license: mit
-datasets:
-- OpenResearcher/OpenResearcher-Dataset
 base_model:
 - nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16
+datasets:
+- OpenResearcher/OpenResearcher-Dataset
 library_name: transformers
+license: mit
+pipeline_tag: text-generation
 ---
+
 <div style="display: flex; align-items: center; justify-content: center; gap: 8px;">
   <img src="imgs/or-logo1.png" style="height: 84px; width: auto;">
   <img src="imgs/openresearcher-title.svg" style="height: 84px; width: auto;">
@@ -13,6 +15,7 @@ library_name: transformers
 
 
 <div align="center">
+    <a href="https://huggingface.co/papers/2603.20278"><img src="https://img.shields.io/badge/arXiv-B31B1B?style=for-the-badge&logo=arXiv&logoColor=white" alt="Paper"></a>
     <a href="https://x.com/DongfuJiang/status/2020946549422031040"><img src="https://img.shields.io/badge/Twitter-000000?style=for-the-badge&logo=X&logoColor=white" alt="Blog"></a>
   <a href="https://boiled-honeycup-4c7.notion.site/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea?source=copy_link"><img src="https://img.shields.io/badge/Blog-4285F4?style=for-the-badge&logo=google-chrome&logoColor=white" alt="Blog"></a>
     <a href="https://github.com/TIGER-AI-Lab/OpenResearcher"><img src="https://img.shields.io/badge/Github-181717?style=for-the-badge&logo=github&logoColor=white" alt="Blog"></a>
@@ -22,7 +25,7 @@ library_name: transformers
   <!-- <a href="https://wandb.ai/dongfu/nano-v3-sft-search"><img src="https://img.shields.io/badge/WandB%20Logs-48B5A3?style=for-the-badge&logo=weightsandbiases&logoColor=white" alt="WandB Logs"></a> -->
   <a href="https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Eval-Logs/tree/main"><img src="https://img.shields.io/badge/Eval%20Logs-755BB4?style=for-the-badge&logo=google-sheets&logoColor=white" alt="Eval Logs"></a> 
 </div>
-</div>
+
 <p align="center">
   🤗 <a href="https://huggingface.co/collections/TIGER-Lab/openresearcher" target="_blank">HuggingFace</a> ｜
 <img src="imgs/notion.svg" width="15px" style="display:inline;"> <a href="https://boiled-honeycup-4c7.notion.site/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea?source=copy_link" target="_blank">Blog</a> ｜ <img src="imgs/slack.png" width="14px" style="display:inline;"> <a href="https://join.slack.com/t/openresearcher/shared_invite/zt-3p0r32cky-PqtZkVjjWIAI14~XwcRMfQ" target="_blank">Slack</a> | <img src="imgs/wechat.svg" width="14px" style="display:inline;"> <a href="https://github.com/TIGER-AI-Lab/OpenResearcher/blob/main/assets/imgs/wechat_group.jpg" target="_blank">WeChat</a> 
@@ -30,7 +33,9 @@ library_name: transformers
 </p>
 
 ## OpenResearcher-30B-A3B Overview
-OpenResearcher-30B-A3B  is an agentic large language model designed for long-horizon deep research  fine-tuned from [NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16) on 96K [OpenResearcher dataset](https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Dataset) with **100+** turns. The dataset is derived by distilling GPT-OSS-120B with [native browser tools](https://docs.vllm.ai/projects/recipes/en/latest/OpenAI/GPT-OSS.html#usage:~:text=Limitation%20section%20below.-,Tool%20Use,-%C2%B6). More info can be found on the dataset card at [OpenResearcher dataset](https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Dataset).
+OpenResearcher-30B-A3B is an agentic large language model designed for long-horizon deep research, presented in the paper [OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis](https://huggingface.co/papers/2603.20278).
+
+It is fine-tuned from [NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-Base-BF16) on 96K [OpenResearcher dataset](https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Dataset) with **100+** turns. The dataset is derived by distilling GPT-OSS-120B with [native browser tools](https://docs.vllm.ai/projects/recipes/en/latest/OpenAI/GPT-OSS.html#usage:~:text=Limitation%20section%20below.-,Tool%20Use,-%C2%B6). More info can be found on the dataset card at [OpenResearcher dataset](https://huggingface.co/datasets/OpenResearcher/OpenResearcher-Dataset).
 
 The model achieves an impressive **54.8%** accuracy on [BrowseComp-Plus](https://huggingface.co/spaces/Tevatron/BrowseComp-Plus), surpassing performance of `GPT-4.1`, `Claude-Opus-4`, `Gemini-2.5-Pro`, `DeepSeek-R1` and `Tongyi-DeepResearch`.
 <div align="center">
@@ -47,18 +52,44 @@ The model achieves an impressive **54.8%** accuracy on [BrowseComp-Plus](https:/
 We evaluate OpenResearcher-30B-A3B across a range of deep research benchmarks, including BrowseComp-Plus, BrowseComp, GAIA, xbench-DeepSearch. Please find more details in [GitHub](https://github.com/TIGER-AI-Lab/OpenResearcher?tab=readme-ov-file#-benchmark-openresearcher).
 
 
-## Quick Start
+## Sample Usage
+
+The following example demonstrates how to use `OpenResearcher-30B-A3B` for deep research within its agentic environment. This requires the tools and environment setup provided in the [official GitHub repository](https://github.com/TIGER-AI-Lab/OpenResearcher).
+
+```python
+import asyncio
+from deploy_agent import run_one, BrowserPool
+from utils.openai_generator import OpenAIAsyncGenerator
+
+async def main():
+    # Initialize generator and browser
+    generator = OpenAIAsyncGenerator(
+        base_url="http://localhost:8001/v1",
+        model_name="OpenResearcher/OpenResearcher-30B-A3B",
+        use_native_tools=True
+    )
+    browser_pool = BrowserPool(search_url=None, browser_backend="serper")
+
+    # Run deep research
+    await run_one(
+        question="What is the latest news about OpenAI?",
+        qid="quick_start",
+        generator=generator,
+        browser_pool=browser_pool,
+    )
 
-We provide a [quick-start](https://github.com/TIGER-AI-Lab/OpenResearcher?tab=readme-ov-file#-quick-start) in GitHub that demonstrates how to use `OpenResearcher-30B-A3B` for deep research.
+    browser_pool.cleanup("quick_start")
 
+if __name__ == "__main__":
+    asyncio.run(main())
+```
 
 ## Citation 
 ```bibtex
-@misc{li2025openresearcher,
-  title={OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis},
-  author={Zhuofeng Li and Dongfu Jiang and Xueguang Ma and Haoxiang Zhang and Ping Nie and Yuyu Zhang and Kai Zou and Jianwen Xie and Yu Zhang and Wenhu Chen},
-  year={2025},
-  howpublished={\url{https://www.notion.so/OpenResearcher-A-Fully-Open-Pipeline-for-Long-Horizon-Deep-Research-Trajectory-Synthesis-2f7e290627b5800cb3a0cd7e8d6ec0ea}},
-  note={Notion Blog}
+@article{li2026openresearcher,
+  title={{OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis}},
+  author={Li, Zhuofeng and Jiang, Dongfu and Ma, Xueguang and Zhang, Haoxiang and Nie, Ping and Zhang, Yuyu and Zou, Kai and Xie, Jianwen and Yu Zhang and Wenhu Chen},
+  journal={arXiv preprint arXiv:2603.20278},
+  year={2026}
 }
 ```