Zikrihakim66/Termining

一个高质量的医疗推理对话合成数据集，使用OpenAI的`gpt-oss-120B`模型生成，推理努力设置为`high`，旨在用于医疗保健应用中大型语言模型的监督微调。数据集涵盖了广泛的医学领域，包括临床医学、基础科学、诊断学、医学教育和研究。每个对话展示了结构化的医学思维和逐步的推理过程。数据集包含200,927个样本，总令牌数为539,165,577，平均每个样本有2,683.3个令牌。

A high-quality synthetic dataset of medical reasoning conversations generated using OpenAIs `gpt-oss-120B` model with reasoning effort set to `high`, designed for supervised fine-tuning of large language models in healthcare applications. The dataset covers a wide range of medical domains including clinical medicine, basic sciences, diagnostics, medical education, and research. Each conversation demonstrates structured medical thinking with step-by-step reasoning processes. The dataset contains 200,927 samples with a total of 539,165,577 tokens, averaging 2,683.3 tokens per sample.