NewstaR/CoTton-uation-3k
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--- license: apache-2.0 task_categories: - question-answering language: - en --- # CoTton-uation 22k / 3k The **CoTton-uation** series is a continuation of the CoTton collective datasets. These releases (**22k** and **3k**) are **not updates** of previous sets, but **additive datasets**. You can freely merge them with earlier CoTton datasets to expand your collection of Chain-of-Thought (CoT) examples. Both sets maintain the same format and design philosophy as prior CoTton datasets: clear, structured CoT annotations for reasoning tasks, curated for consistency and usability. --- ## FAQ **Q: Is this dataset the same as other CoTton datasets?** **A:** No. These datasets do not overlap with the earlier CoTton releases. They are not replacements or updates. Instead, they are designed to be additive, so you can merge them with prior CoTton datasets for broader coverage. --- **Q: Does this dataset include all the planned CoT datasets?** **A:** Not yet. Several planned datasets are still missing, and we aim to release them in the future. In particular, we want to add the following NVIDIA-related datasets and others. --- **Q: Should I use this dataset alone or merge it with others?** **A:** You can use CoTton-uation 22k or 3k on their own. However, they are most useful when merged with the earlier CoTton datasets to create a more complete and powerful set of CoT examples.
--- license: Apache 2.0 task_categories: - 问答（question-answering） language: - 英语 --- # CoTton-uation 22k / 3k **CoTton-uation**系列是CoTton集体数据集的续作。 本次发布的**22k**与**3k**版本并非旧数据集的更新迭代，而是全新的增补数据集。您可将其与此前发布的CoTton数据集自由合并，以扩充您的思维链（Chain-of-Thought, CoT）示例样本库。 两个版本均延续了此前CoTton数据集的格式与设计理念：针对推理任务设计清晰、结构化的CoT标注，经精心筛选以保证标注一致性与可用性。 --- ## 常见问题解答 **问：本数据集与其他CoTton数据集是否一致？** **答：否。本数据集与此前发布的CoTton系列数据集无重叠内容，既非替代版本也非更新版本。其设计初衷为增补型数据集，可与旧版CoTton数据集合并以覆盖更广泛的任务场景。** --- **问：本数据集是否包含所有规划中的CoT相关数据集？** **答：尚未完全覆盖。目前仍有多项规划中的数据集尚未发布，团队计划在未来逐步推出。具体而言，我们拟新增以下与NVIDIA相关的数据集及其他类型数据集。** --- **问：本数据集应单独使用，还是与其他数据集合并使用？** **答：CoTton-uation 22k或3k版本均可独立使用。但将其与旧版CoTton数据集合并后，可构建更完整、更高效的CoT示例样本集，从而发挥最大效用。**
