lightonai/Dolci-Think-SFT-32B-Multilingual

Dolci-Think-SFT-32B-Multilingual 是一个大规模的多语言长链思维推理语料库，涵盖六种语言：英语、法语、德语、西班牙语、中文和斯瓦希里语。每个样本包含一个问题、一个长形式的推理轨迹和一个最终答案，所有内容均翻译成目标语言，序列长度可达32,768个标记。该数据集随论文《Rethinking the Multilingual Reasoning Gap with Layer Swap》发布。源语料库为allenai/Dolci-Think-SFT-32B，语言包括英语（源语言）和五种翻译语言，每种语言约有50万样本，最大序列长度为32,768个标记，使用google/gemma-3-27b-it模型进行翻译。数据集中，英语源语料混合了七个任务类别，以数学和代码为主，各语言样本数量和标记量统计详细，例如英语样本485,873个，平均标记10,848，总标记5.27B。此外，还列出了基于该数据集训练的模型，包括各语言的原生专家模型、英语枢纽专家模型和层交换模型。

Dolci-Think-SFT-32B-Multilingual is a large-scale multilingual long chain-of-thought (CoT) reasoning corpus spanning six languages: English, French, German, Spanish, Chinese, and Swahili. Each sample includes a question, a long-form reasoning trace, and a final answer, all translated into the target language, with sequences up to 32,768 tokens. It is released alongside the paper Rethinking the Multilingual Reasoning Gap with Layer Swap. The source corpus is allenai/Dolci-Think-SFT-32B, with languages including English (source) plus five translated languages, approximately 500k samples per language, max sequence length of 32,768 tokens, and translation model google/gemma-3-27b-it. The English source mixes seven task categories dominated by math and code, with per-language statistics provided (e.g., English: 485,873 samples, mean tokens 10,848, total tokens 5.27B). Models trained on this dataset include native specialists, English-pivoted specialists, and Layer Swap models for each language.