File size: 3,185 Bytes
47e8a01 3f00c3e 47e8a01 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
---
license: apache-2.0
datasets:
- Agent-Ark/Toucan-1.5M
language:
- en
base_model:
- Qwen/Qwen2.5-7B-Instruct
tags:
- agent
---
# 🦤 Toucan-1.5M:
Toucan-1.5M is the largest fully synthetic tool-agent dataset to date, designed to advance tool use in agentic LLMs. It comprises over 1.5 million trajectories synthesized from 495 real-world Model Context Protocols (MCPs) spanning 2,000+ tools. By leveraging authentic MCP environments, Toucan-1.5M generates diverse, realistic, and challenging tasks requires using multiple tools, with trajectories involving real tool executions across multi-round, multi-turn, sequential, and parallel tool calls. Models fine-tuned on Toucan-1.5M outperform much larger closed-source counterparts on the BFCL V3 benchmark and extend the Pareto frontier on the MCP-Universe benchmark.
- 📄 [Technical Report](https://arxiv.org/abs/2510.01179) - Discover the methodology and technical details behind Toucan-1.5M
- 💾 [Github Repo](https://github.com/TheAgentArk/Toucan) - Access the complete pipeline used to produce Toucan-1.5M
- 🤗 [HF Dataset](https://huggingface.co/datasets/Agent-Ark/Toucan-1.5M) - Full dataset (You are here!)
- 🤖 Model Checkpoints - [Qwen2.5-7B](https://huggingface.co/Agent-Ark/Toucan-Qwen2.5-7B-Instruct-v0.1) | [Qwen2.5-14B](https://huggingface.co/Agent-Ark/Toucan-Qwen2.5-7B-Instruct-v0.1) | [Qwen2.5-32B](https://huggingface.co/Agent-Ark/Toucan-Qwen2.5-32B-Instruct-v0.1)
## About This Model
This model is a fine-tuned variant of **Qwen2.5-7B-Instruct**, trained on a curated subset of the [Toucan-1.5M](https://huggingface.co/datasets/Agent-Ark/Toucan-1.5M) dataset. The supervised fine-tuning (SFT) subset consists of **119.3K instances** in total, including:
- **28.3K** from the original pipeline
- **40K** from Extension 1 (*Irrelevance*)
- **15.8K** from Extension 2 (*Diversify*)
- **35.2K** from Extension 3 (*Multi-Turn*)
We adopt the `Hermes` prompt template for fine-tuning. For a detailed description of the training setup and hyperparameters, please refer to our [technical report](https://arxiv.org/abs/2510.01179).
## Model Performance
Toucan-1.5M remarkably improves baseline model performance through SFT and enables smaller models to outperform larger models across different evaluation aspects, as evidenced in BFCL-V3 and MCP Universe benchmarks.
## 📚 Citation
If you find the data or code useful, please cite:
```
@misc{xu2025toucan,
title={TOUCAN: Synthesizing 1.5M Tool-Agentic Data from Real-World MCP Environments},
author={Zhangchen Xu and Adriana Meza Soria and Shawn Tan and Anurag Roy and Ashish Sunil Agrawal and Radha Poovendran and Rameswar Panda},
year={2025},
eprint={2510.01179},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2510.01179},
}
```
**Contact**: For questions, please contact [Zhangchen](mailto:zxu9@uw.edu) by email. |