gabrielchua/off-topic

该数据集由合成的LLM系统提示与用户提示配对组成，并分类为离题或相关。其目的是提供反映大型语言模型（LLMs）在实际使用中的示例，适用于开放性和封闭性任务，如文本生成和分类。数据集可用于训练和基准测试离题防护机制。数据集包含系统提示、用户提示和离题分类标签。系统提示设定了交互的上下文或主题，用户提示则与系统提示交互，内容可能相关或无关。离题标签为二进制分类，表示用户提示是否偏离系统提示的上下文。

This dataset consists of synthetic LLM system prompts paired with user prompts, classified as either off-topic or on-topic. The aim is to provide realistic, real-world-inspired examples reflecting how large language models (LLMs) are used today for both open-ended and closed-ended tasks, such as text generation and classification. This dataset can be used for training and benchmarking off-topic guardrails. The dataset was generated using real-world system prompts and random words as seeds with an LLM. The dataset structure includes system prompts, user prompts, and off-topic classification labels.