alucent/mirror-XLAM-7.5k-Irrelevance

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 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:… See the full description on the dataset page: https://huggingface.co/datasets/alucent/mirror-XLAM-7.5k-Irrelevance.