Reasoning Base 20k Reasoning Base Dataset

This dataset is designed to train reasoning models so that they can think about complex problems like humans and then respond. The dataset includes a variety of questions from different fields (science, coding, mathematics, etc.), each with a detailed chain of ideas (COT) and the correct answer. The goal is to enable the model to learn and improve its reasoning process, identify and correct errors, and provide high-quality, detailed responses. The dataset is still under development.

Dataset structure

Data Fields

• User: The user's query or problem statement.
• assistant: The correct answer to the question.
• reasoning: A detailed, step-by-step reasoning process that explains how to arrive at the correct answer.
• template: Pre-applied RChatML chat template.