Reasoning Base 20k 推理基数数据集

该数据集旨在训练推理模型，让模型可以像人类一样思考复杂的问题，然后再做出反应。数据集包括来自不同领域（科学、编码、数学等）的各种问题，每个问题都有详细的思路链 (COT) 和正确答案。目标是使模型能够学习和改进其推理过程，识别和纠正错误，并提供高质量、详细的响应。该数据集目前仍在开发中。

This dataset is designed for training reasoning models, empowering them to deliberate over complex problems in a human-like manner before generating appropriate responses. It encompasses a wide range of questions across diverse domains such as science, coding, mathematics and more, with each question paired with a detailed chain-of-thought (COT) reasoning process and the correct final answer. The core goal is to enable models to learn and refine their reasoning procedures, identify and correct errors, and provide high-quality, detailed responses. This dataset is currently under active development.

搜集汇总

背景与挑战

背景概述

该数据集用于训练推理模型，使其能够模拟人类思考复杂问题，涵盖科学、编码和数学等多个领域的问题，每个问题均提供详细的思路链和正确答案。其目标是帮助模型学习和优化推理过程，识别并纠正错误，从而生成高质量的详细响应，目前该数据集仍在持续开发中。