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Model: wanglab/bioreason-pro-rl Source: Original Platform
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78
README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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tags:
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- protein
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- gene-ontology
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- function-prediction
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- biology
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- bioinformatics
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- reasoning
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- reinforcement-learning
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- grpo
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datasets:
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- wanglab/bioreason-pro-rl-reasoning-data
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---
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<h1 align="center">
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🧬 BioReason-Pro<br>Advancing Protein Function Prediction with<br>Multimodal Biological Reasoning
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</h1>
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<p align="center">
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<a href="https://www.biorxiv.org/content/10.64898/2026.03.19.712954v1" target="_blank"><img src="https://img.shields.io/badge/bioRxiv-2026.03.19.712954-FF6B6B?style=for-the-badge&logo=arxiv&logoColor=white" alt="bioRxiv"></a>
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<a href="https://github.com/bowang-lab/BioReason-Pro"><img src="https://img.shields.io/badge/GitHub-Code-4A90E2?style=for-the-badge&logo=github&logoColor=white" alt="GitHub"></a>
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<a href="https://bioreason.net"><img src="https://img.shields.io/badge/Website-Online-00B89E?style=for-the-badge&logo=internet-explorer&logoColor=white" alt="Website"></a>
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<a href="https://huggingface.co/collections/wanglab/bioreason-pro"><img src="https://img.shields.io/badge/HuggingFace-Models & Data-FFBF00?style=for-the-badge&logo=huggingface&logoColor=white" alt="HuggingFace"></a>
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</p>
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<br>
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## BioReason-Pro RL
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Reinforcement learning (GRPO) optimized checkpoint of BioReason-Pro, a multimodal reasoning LLM for protein function prediction. This model builds on the SFT checkpoint and is further optimized through group relative policy optimization to improve reasoning quality and GO term prediction accuracy.
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<div align="center" style="background-color: #1a1a2e; border: 2px solid #00B89E; border-radius: 12px; padding: 20px 30px; margin: 20px 0;">
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<h3 style="color: white;">🚀 Getting Started</h3>
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<p style="color: white;"><b>Check out the GitHub repo for full setup instructions and local inference guide:</b></p>
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<a href="https://github.com/bowang-lab/BioReason-Pro">
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<img src="https://img.shields.io/badge/Setup_Guide-GitHub-4A90E2?style=for-the-badge&logo=github&logoColor=white" alt="Setup Guide">
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</a>
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</div>
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**Training data:** [wanglab/bioreason-pro-rl-reasoning-data](https://huggingface.co/datasets/wanglab/bioreason-pro-rl-reasoning-data)
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See also:
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- [BioReason-Pro SFT](https://huggingface.co/wanglab/bioreason-pro-sft) - supervised fine-tuned checkpoint
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- [GO-GPT](https://huggingface.co/wanglab/gogpt) - autoregressive GO term predictor
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## Citation
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If you find this work useful, please cite our papers:
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```bibtex
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@article {Fallahpour2026.03.19.712954,
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author = {Fallahpour, Adibvafa and Seyed-Ahmadi, Arman and Idehpour, Parsa and Ibrahim, Omar and Gupta, Purav and Naimer, Jack and Zhu, Kevin and Shah, Arnav and Ma, Shihao and Adduri, Abhinav and G{\"u}loglu, Talu and Liu, Nuo and Cui, Haotian and Jain, Arihant and de Castro, Max and Fallahpour, Amirfaham and Cembellin-Prieto, Antonio and Stiles, John S. and Nem{\v c}ko, Filip and Nevue, Alexander A. and Moon, Hyungseok C. and Sosnick, Lucas and Markham, Olivia and Duan, Haonan and Lee, Michelle Y. Y. and Salvador, Andrea F. M. and Maddison, Chris J. and Thaiss, Christoph A. and Ricci-Tam, Chiara and Plosky, Brian S. and Burke, Dave P. and Hsu, Patrick D. and Goodarzi, Hani and Wang, Bo},
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title = {BioReason-Pro: Advancing Protein Function Prediction with Multimodal Biological Reasoning},
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elocation-id = {2026.03.19.712954},
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year = {2026},
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doi = {10.64898/2026.03.19.712954},
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publisher = {Cold Spring Harbor Laboratory},
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URL = {https://www.biorxiv.org/content/early/2026/03/20/2026.03.19.712954},
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eprint = {https://www.biorxiv.org/content/early/2026/03/20/2026.03.19.712954.full.pdf},
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journal = {bioRxiv}
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}
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@misc{fallahpour2025bioreasonincentivizingmultimodalbiological,
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title={BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model},
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author={Adibvafa Fallahpour and Andrew Magnuson and Purav Gupta and Shihao Ma and Jack Naimer and Arnav Shah and Haonan Duan and Omar Ibrahim and Hani Goodarzi and Chris J. Maddison and Bo Wang},
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year={2025},
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eprint={2505.23579},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2505.23579},
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}
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```
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30
added_tokens.json
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added_tokens.json
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||||
{
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||||
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||||
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84
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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||||
{%- for message in messages[::-1] %}
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||||
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||
{%- if ns.multi_step_tool and message.role == "user" and not(message.content is string and message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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||||
{%- endfor %}
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||||
{%- for message in messages %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' }} {%- if message.content is string %}{{- message.content + '<|im_end|>' + '\n' }}{%- else %}{%- for content in message.content %}{%- if content.type == 'protein' or 'protein' in content %}{{- "Protein: <|protein_pad|>\n\n" }}{%- elif content.type == 'go_graph' or 'go_graph' in content %}{{- "GO graph: <|go_graph_pad|>\n\n" }}{%- elif 'text' in content %}{{ content.text }}{%- endif %}{%- endfor %}{{- '<|im_end|>' + '\n' }}{%- endif %}{%- elif message.role == "assistant" %}
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{%- set content = message.content[0].text %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
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{%- set reasoning_content = message.reasoning_content %}
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||||
{%- else %}
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||||
{%- if '</think>' in message.content %}
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{%- set content = message.content[0].text.split('</think>')[-1].lstrip('\n') %}
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{%- set reasoning_content = message.content[0].text.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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||||
{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
|
||||
{%- if tool_call.function %}
|
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{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
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{{- tool_call.arguments }}
|
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{%- endif %}
|
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{{- '<|im_end|>\n' }}
|
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{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
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{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
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{{- '\n<tool_response>\n' }}
|
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{{- message.content }}
|
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{{- '\n</tool_response>' }}
|
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
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{{- '<|im_end|>\n' }}
|
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{%- endif %}
|
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{%- endif %}
|
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{%- endfor %}
|
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{%- if add_generation_prompt %}
|
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{{- '<|im_start|>assistant\n' }}
|
||||
{%- if enable_thinking is defined and enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
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68
config.json
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config.json
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{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
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],
|
||||
"attention_bias": false,
|
||||
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|
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|
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"dtype": "float32",
|
||||
"eos_token_id": 151645,
|
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"head_dim": 128,
|
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"hidden_act": "silu",
|
||||
"hidden_size": 2560,
|
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"initializer_range": 0.02,
|
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"intermediate_size": 9728,
|
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"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 262144,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 5000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"transformers_version": "4.57.3",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151671
|
||||
}
|
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generation_config.json
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generation_config.json
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{
|
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"bos_token_id": 151643,
|
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"do_sample": true,
|
||||
"eos_token_id": [
|
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151645,
|
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151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
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"temperature": 0.6,
|
||||
"top_k": 20,
|
||||
"top_p": 0.95,
|
||||
"transformers_version": "4.57.3"
|
||||
}
|
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3
go-basic.obo
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go-basic.obo
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version https://git-lfs.github.com/spec/v1
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oid sha256:0c0062efbb1b199a6a54e62c0c48ff0038d39173aecc7edfab66a20090d5ec2d
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size 30992530
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go_embedding.pt
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go_embedding.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:19dc53fc652be73ef31979d774ba42c207d09b04762fc9395f16943b8882e755
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size 1025612
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go_encoder.pt
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go_encoder.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:591890013adae365d60b00aaf75cf46a80bb11d565ca79c7e37fe545d5b8e820
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size 330426869
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3
go_projection.pt
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go_projection.pt
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version https://git-lfs.github.com/spec/v1
|
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oid sha256:2dc979b0364981d001a610e857760f63dd9d2b955fa3ce6bac5957f2b85ec239
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size 52451865
|
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151388
merges.txt
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151388
merges.txt
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Load Diff
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missing_and_unexpected_keys.txt
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missing_and_unexpected_keys.txt
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Missing keys:
|
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go_encoder.gat_layers.0.att_src
|
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go_encoder.gat_layers.0.att_dst
|
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go_encoder.gat_layers.0.bias
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go_encoder.gat_layers.0.lin.weight
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go_encoder.gat_layers.1.att_src
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go_encoder.gat_layers.1.att_dst
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go_encoder.gat_layers.1.bias
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go_encoder.gat_layers.1.lin.weight
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go_encoder.gat_layers.2.att_src
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go_encoder.gat_layers.2.att_dst
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go_encoder.gat_layers.2.bias
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go_encoder.gat_layers.2.lin.weight
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go_encoder.output_projection.0.weight
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3
protein_projection.pt
Normal file
3
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Normal file
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|
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special_tokens_map.json
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26
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Normal file
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3
tokenizer.json
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3
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244
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1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user