MadeAgents/xlam-irrelevance-7.5k

--- license: cc-by-4.0 --- # xlam-irrelevance-7.5k ## Overview The **xlam-irrelevance-7.5k** is a specialized dataset designed to activate the ability of irrelevant function detection for large language models (LLMs). ## Source and Construction This dataset is built upon [xlam-function-calling-60k](https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k) dataset, from which we random sampled 7.5k instances, removed the ground truth function from the provided tool list, and relabel them as irrelevant. For more details, please refer to [Hammer: Robust Function-Calling for On-Device Language Models via Function Masking](https://arxiv.org/abs/2410.04587) and [Hammer GitHub repository](https://github.com/MadeAgents/Hammer) . ## Application This dataset is a supplement to the xLAM dataset. After integrating the data from these two parts, we trained the [Hammer series](https://huggingface.co/MadeAgents) of models.--- license: cc-by-4.0 --- # xlam-irrelevance-7.5k ## 概述 **xlam-irrelevance-7.5k** 是一款专为激活大语言模型（Large Language Model）无关功能检测能力打造的专用数据集。 ## 来源与构建 本数据集基于 [xlam-function-calling-60k](https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k) 数据集构建：我们从中随机采样7.5千条样本，将给定工具列表中的基准真值函数移除，并将这些样本重新标注为无关项。更多细节可参阅论文《Hammer: Robust Function-Calling for On-Device Language Models via Function Masking》（https://arxiv.org/abs/2410.04587）以及 [Hammer GitHub 仓库](https://github.com/MadeAgents/Hammer)。 ## 应用 本数据集是 xLAM 数据集的补充。在将二者的数据进行整合后，我们训练了 [Hammer 系列](https://huggingface.co/MadeAgents) 模型。