🚀 DeepHermes Tool Calling Specialist - Atropos RL
The DeepHermes Tool Calling Specialist - Atropos RL model is an experimental fine - tuned model that significantly enhances the tool - calling performance of the base model during reasoning mode.
🚀 Quick Start
The DeepHermes Tool Calling Specialist - Atropos RL model is an experimental artifact fine - tuned by Nous Research using our innovative open - source reinforcement learning framework—Atropos. This variant specifically improves the tool calling performance of the DeepHermes 3 Llama - 3.1 8B model during its reasoning mode.
⚠️ Important Note
This model is intended as an experimental artifact and is not designed for broad, general - purpose use.
✨ Features
- Improved Tool Calling in Reasoning Mode: Reinforcement learning significantly boosts tool usage during complex reasoning tasks.
- Open - Source RL Framework: Utilizes the fully open - source Atropos RL Environments.
- Active Open Source Community: Contributions welcomed on the Atropos GitHub.
- Upcoming SOTA RL Trainer: A state - of - the - art open - source reinforcement learning trainer by Nous Research is coming soon.
📦 Installation
No installation steps are provided in the original document, so this section is skipped.
💻 Usage Examples
This model supports multiple inference modes including:
- Reasoning (Deep Thinking Mode)
- Standard Chat/Instruction Mode
- Structured JSON Outputs
- Function Calling
Note: You must first place DeepHermes' reasoning system prompt, and then append your function calling system prompt after for it to do reasoning and tool calling simultaneously.
🌐 Hermes Function Calling GitHub
📚 Documentation
Atropos Open Source Framework
Atropos is Nous Research’s open - source Reinforcement Learning environment stack, designed to enhance various aspects of LLM functionalities through structured RL methodologies. We encourage contributions and exploration:
🌐 Atropos GitHub Repository
Benchmark Results
Evaluations on the Berkeley Function Calling benchmark demonstrate significant improvements in tool calling accuracy during reasoning mode, compared to its base model:
Benchmark |
Base Accuracy |
Atropos RL Accuracy |
Improvement |
Parallel |
0.10 |
0.46 |
4.6x |
Simple |
0.21 |
0.5175 |
2.5x |
These enhancements are due to RL fine - tuning specifically targeted at improving reasoning - based tool calling capabilities.
Eval set accuracy results:

🔧 Technical Details
No specific technical details beyond what's already covered are provided in the original document, so this section is skipped.
📄 License
This model is under the llama3
license.
📋 Information Table
Property |
Details |
Model Type |
DeepHermes Tool Calling Specialist - Atropos RL |
Base Model |
meta - llama/Meta - Llama - 3.1 - 8B |
Library Name |
transformers |
Tags |
Llama - 3, RL, Atropos, Tool Calling, Nous Research, instruct, finetune, reasoning, function calling, transformers, reinforcement - learning, json mode, chatml |
📚 Citation
@misc{
title={DeepHermes Tool Calling Specialist - Atropos RL},
author={Teknium and Dakota Mahan and Roger Jin and Chen Guang and Jai Suphavadeeprasit and Jeffrey Quesnelle},
year={2025},
url={https://huggingface.co/NousResearch/DeepHermes-Tool-Calling-Specialist-Atropos-RL}
}
👥 Community and Support
For questions, issues, or findings, please open issues or discussions in the respective GitHub repositories:
Nous Research encourages active community engagement and open - source contributions to continuously improve model performance and capabilities.