90 lines
2.9 KiB
Markdown
90 lines
2.9 KiB
Markdown
---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- tool-use
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- agent
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- retrieval
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- reinforcement-learning
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- qwen3
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- toolomni
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base_model: Qwen/Qwen3-4B
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model_name: ToolOmni
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---
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# ToolOmni
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[](https://arxiv.org/abs/2604.13787)
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[](https://github.com/Huangsz2021/ToolOmni)
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[](#license)
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ToolOmni is a tool-use language model released for the ACL 2026 Main Conference paper *ToolOmni: Enabling Open-World Tool Use via Agentic Learning with Proactive Retrieval and Grounded Execution*.
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This checkpoint is built on top of **Qwen/Qwen3-4B-Instruct** and is designed for **open-world tool use**. The model is trained to proactively retrieve relevant tools and generate grounded multi-step tool calls for downstream task completion.
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## Model Description
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- Model type: Causal language model for tool use
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- Base model: `Qwen/Qwen3-4B-Instruct`
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- Paper venue: ACL 2026 Main Conference
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- Codebase: training, evaluation, retrieval, and tool execution utilities are available in the public repository
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## Intended Uses
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This model is intended for:
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- research on tool-use agents
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- benchmarking open-world tool retrieval and grounded execution
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- studying retrieval-augmented and execution-aware training
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- reproducing the ToolOmni evaluation pipeline
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The model is expected to work best together with the ToolOmni codebase, retriever, and tool execution environment.
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## Training
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ToolOmni follows an agentic learning framework with:
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- proactive tool retrieval
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- grounded tool execution
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- reinforcement learning for multi-step tool-use behavior
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The training and evaluation pipeline is released in the ToolOmni repository.
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## Evaluation
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ToolOmni is evaluated on ToolBench-style benchmarks in both:
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- with-api-list / golden-tool settings
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- open-domain settings without golden tool lists
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Please refer to the project repository and paper for the detailed evaluation protocol and benchmark results.
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## Repository
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- Paper: https://arxiv.org/abs/2604.13787
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- Code: https://github.com/Huangsz2021/ToolOmni
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- Model: https://huggingface.co/bue0912/ToolOmni-Qwen3-4B
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- Dataset: https://huggingface.co/datasets/bue0912/ToolOmni-Data
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- Collection: https://huggingface.co/collections/bue0912/toolomni
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## Citation
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```bibtex
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@misc{huang2026toolomnienablingopenworldtool,
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title={ToolOmni: Enabling Open-World Tool Use via Agentic learning with Proactive Retrieval and Grounded Execution},
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author={Shouzheng Huang and Meishan Zhang and Baotian Hu and Min Zhang},
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year={2026},
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eprint={2604.13787},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2604.13787},
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}
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```
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## License
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This release is aligned with **Apache-2.0**. See the repository-level [LICENSE](https://github.com/Huangsz2021/ToolOmni/blob/main/LICENSE) for details.
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