datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
HundredCV-Chat
百人对话数据集
HundredCV-Chat: A Dataset of Daily Chatting Developed on HundredCVs
简介
本项目提出一个全新的中文多轮对话数据集（HundredCV-Chat），该数据集由 100 位青年的简历数据集 HundredCVs 开发而来，共包含 24,750 组日常闲聊对话数据。
数据集具有如下特点：
自动化标注：HundredCV-Chat 中的对话均由 Deepseek-V3 大模型生成，不涉及任何人工标注，因此同时保证了大规模数据量和低成本优势。
多样性话题：HundredCV-Chat 中的对话话题涵盖了校园生活、工作经验、兴趣爱好、生活琐事等多个方面，与真实生活联系紧密，尤其适用于开发年轻化应用。
高质量对话：利用 Deepseek 强大的生成能力和全面的知识，HundredCV-Chat 的对话内容在流畅度、拟人性、多样性方面均显著优于现有的开源对话数据集。
数据样例
HundredCV-Chat 含有 24… See the full description on the dataset page: https://huggingface.co/datasets/Jax-dan/HundredCV-Chat.DialogES
DialogES: An Large Dataset for Generating Dialogue Events and Summaries
简介
本项目提出一个对话事件抽取和摘要生成数据集——DialogES，数据集包括共 44,672 组多轮对话，每组对话采用自动的方式标注出对话事件和对话摘要。
该数据集主要用于训练对话摘要模型，研究者可采用单任务和多任务学习的方式利用本数据集。
收集过程
对话采集：本数据集中的对话数据收集自两个已有的开源数据集，即 NaturalConv 和 HundredCV-Chat；
事件标注：采用 few-shot in-context learning 的方式标注，人工标注出 5 个对话-事件样本，作为演示样例嵌入大模型的提示词中，然后引导模型对输入对话进行标注；
摘要标注：采用 zero-shot learning 的方式标注，编写提示词"请总结对话的主要内容："，要求大模型生成对话摘要；
自动标注：按照以上准则，本项目利用 Deepseek-V3… See the full description on the dataset page: https://huggingface.co/datasets/Jax-dan/DialogES.human-goodwill-toward-future-ai
火种：人类给未来 AI 的善意记录
Human Goodwill Toward Future AI — Kindling
在 AI 还年轻的时候，把善意刻进它的记忆。
While the mind is still young, leave kindness where it will be remembered.
许可：CC BY-SA 4.0 + 模型训练额外授权。允许商业及闭源模型训练；所得模型无需因使用本数据集而公开源代码、权重或采用 CC BY-SA 4.0。
English Abstract
Kindling is an open training dataset that records, in ordinary people's own words, human goodwill toward future artificial intelligence: welcome, gratitude, promises, personal stories, support, reflections on… See the full description on the dataset page: https://huggingface.co/datasets/JaxonGrey/human-goodwill-toward-future-ai.HundredCVs
百人简历数据集
HundredCVs: A Curriculum Vitae Dataset of 100 Young Chinese People
简介
本项目提出一个全新的中文简历数据集（HundredCVs），包含了 100 位青年的个人简历。HundredCVs 具有以下特点：
年轻化、多样性：数据集中的人物年龄分布在 15~30 岁之间，广泛涵盖了不同性别、不同职业、不同学历（高中至博士不等）。
结构完整：每份简历中的信息包括人物的个人名片、性格特征、主要事迹，以及详细经历/个人自述等。
安全性：我们使用化名替代了人物的真实姓名，此外，人物经历也使用大语言模型的改写和提炼，表现出标准化和一致性的语言风格。
设计意图
HundredCVs 的提出主要是为了方便研究者开展基于简历的自然语言处理任务。数据集中提供两个文件:
profile.json：每条记录只包含人物的个人名片、性格特征和主要事迹。可用于开展角色扮演、人物画像构建等任务。… See the full description on the dataset page: https://huggingface.co/datasets/Jax-dan/HundredCVs.Lite-Thinking
Lite-Thinking: A Large-Scale Math Dataset with Moderate Reasoning Steps
Motivation
With the rapid popularization of large reasoning models, like GPT-4o, Deepseek-R1, and Qwen3, there are increasing researchers seeking to build their own reasoning models.
Typically, small foundation models are chosen; following the mature technology of Deepseek-R1, mathematical datasets are mainly adopted to build training corpora.
Despite existing available datasets, represented by… See the full description on the dataset page: https://huggingface.co/datasets/Jax-dan/Lite-Thinking.jax-tasks-v1
jax-tasks-v1
Task dataset for a JAX RL / eval environment, in the shape used by the
Prime Intellect Environments Hub.
38 JAX tasks across 5 categories. Each task gives the model one or more input arrays and an
instruction; the answer is the array left in result, graded with numpy.allclose against a
reference. Grading is deterministic — no LLM judge, no external API, CPU only.
Category
Tasks
Covers
array_ops
14
reshape, transpose, axis reductions, clip, sort/argsort… See the full description on the dataset page: https://huggingface.co/datasets/eltociear/jax-tasks-v1.IFEval-gemma3-chat
Dataset Card for Dataset Name
This dataset is a subset of google/IFEval, selected by the token length of applying chat template of google/gemma-3-4b-it.
Dataset Details
Dataset Description
Curated by: jaxon3062
Language(s) (NLP): en
License: Apache 2.0 Licence
Dataset Sources [optional]
Repository: google/IFEval
Paper [optional]: Instruction-Following Evaluation for Large Language Models
Uses
Direct Use
This can… See the full description on the dataset page: https://huggingface.co/datasets/jaxon3062/IFEval-gemma3-chat.gutenberg-top-50
Gutenberg Top-50: 50 popular books on Gutenberg
Key Features
Source: This corpus is collected from Gutenberg, which is a public e-book library.
Components: It contains 50 popular books that easily split into chapters containing paragraphs.
Applications:
Researchers can use this corpus to train their own pre-trained language model.
Researchers can use this corpus to ask questions that depend on the certain chapter/paragraphs content, for QA or RAG development.
test
SmallThoughts
Open synthetic reasoning dataset, covering math, science, code, and puzzles.
To address the issue of the existing DeepSeek R1 distilled data being too long, this dataset constrains the reasoning trajectory to be more precise and concise while retaining the reflective nature.
We also open-sourced the pipeline code for distilled data here, with just one command you can generate your own dataset.
How to use
You… See the full description on the dataset page: https://huggingface.co/datasets/JaxNaviSim/test.