Team-ACE/ToolACE

--- license: apache-2.0 task_categories: - text-generation language: - en - zh tags: - synthetic - tools size_categories: - 10K<n<100K --- # ToolACE ToolACE is an automatic agentic pipeline designed to generate Accurate, Complex, and divErse tool-learning data. ToolACE leverages a novel self-evolution synthesis process to curate a comprehensive API pool of 26,507 diverse APIs. Dialogs are further generated through the interplay among multiple agents, guided by a formalized thinking process. To ensure data accuracy, we implement a dual-layer verification system combining rule-based and model-based checks. More details can be found in our paper on arxiv: [*ToolACE: Winning the Points of LLM Function Calling*](https://arxiv.org/abs/2409.00920). The model finetuned with ToolACE is released in [hf](https://huggingface.co/Team-ACE/ToolACE-8B), winning promising scores on the functional calling leaderboard [BFCL](https://gorilla.cs.berkeley.edu/leaderboard.html#leaderboard).  ### Citation If you think ToolACE is useful in your work, please cite our paper: ``` @misc{liu2024toolacewinningpointsllm, title={ToolACE: Winning the Points of LLM Function Calling}, author={Weiwen Liu and Xu Huang and Xingshan Zeng and Xinlong Hao and Shuai Yu and Dexun Li and Shuai Wang and Weinan Gan and Zhengying Liu and Yuanqing Yu and Zezhong Wang and Yuxian Wang and Wu Ning and Yutai Hou and Bin Wang and Chuhan Wu and Xinzhi Wang and Yong Liu and Yasheng Wang and Duyu Tang and Dandan Tu and Lifeng Shang and Xin Jiang and Ruiming Tang and Defu Lian and Qun Liu and Enhong Chen}, year={2024}, eprint={2409.00920}, archivePrefix={arXiv}, primaryClass={cs.LG}, url={https://arxiv.org/abs/2409.00920}, } ```

搜集汇总

背景与挑战

背景概述

ToolACE是一个自动化的工具学习数据集，旨在提升大型语言模型的函数调用能力。它通过自进化合成过程构建了包含26,507个多样化API的池，并利用多代理交互生成对话数据，同时采用规则和模型双重验证确保数据准确性。该数据集微调的模型在BFCL函数调用排行榜上取得了显著成绩。