TNSA/OpenReasoner-V1

OpenReasoner-V1是一个高保真、统一的数据集，专为微调高级推理模型而设计。它结合了复杂的数学问题解决和高质量的通用指令数据，特别针对NGen-4 Lite等先进的小型语言模型进行了优化。数据集包含22万多个数学问题及其详细的逐步解决方案，以提升逻辑推理能力；融合了OpenHermes-2.5指令集，确保模型保持优秀的通用对话能力和广泛知识；还包含用<think>标签格式化的蒸馏推理轨迹，旨在教导模型在复杂场景中“先思考后行动”。所有数据均以标准的多轮对话格式提供，可直接用于监督微调（SFT）流程。OpenReasoner-V1 is a high-fidelity, unified dataset designed for fine-tuning advanced reasoning models. It combines complex mathematical problem-solving with high-quality general instruction data, specifically optimized for state-of-the-art small language models like NGen-4 Lite. The dataset includes 220k+ mathematical problems with detailed, step-by-step solutions to improve logical deduction capabilities; is infused with the OpenHermes-2.5 instruction set to ensure the model maintains excellent general-purpose conversational abilities and broad knowledge; and features distilled reasoning trajectories formatted with <think> tags, designed to teach models how to reason-before-acting in complex scenarios. All data is provided in a standard multi-turn conversation format, ready for immediate use in SFT (Supervised Fine-Tuning) pipelines.