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

Hi there! I'm Niels from the community science team at Hugging Face.

This PR improves your model card with the following:
- Adds the `pipeline_tag: text-generation` to the metadata for better Hub discoverability.
- Adds a direct link to the associated research paper: [OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis](https://huggingface.co/papers/2603.20278).
- Includes a sample usage section based on the code provided in your GitHub repository.

These changes help users find and use your model more effectively. Feel free to merge if this looks good!

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}
 }
 ```