datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
AM-DeepSeek-R1-Distilled-1.4MFor more open-source datasets, models, and methodologies, please visit our GitHub repository.
AM-DeepSeek-R1-Distilled-1.4M is a large-scale general reasoning task dataset composed of
high-quality and challenging reasoning problems. These problems are collected from numerous
open-source datasets, semantically deduplicated, and cleaned to eliminate test set contamination.
All responses in the dataset are distilled from the reasoning model (mostly DeepSeek-R1) and have undergone
rigorous… See the full description on the dataset page: https://huggingface.co/datasets/a-m-team/AM-DeepSeek-R1-Distilled-1.4M.AM-DeepSeek-R1-0528-Distilled
📘 Dataset Summary
This dataset is a high-quality reasoning corpus distilled from DeepSeek-R1-0528, an improved version of the DeepSeek-R1 large language model. Compared to its initial release, DeepSeek-R1-0528 demonstrates significant advances in reasoning, instruction following, and multi-turn dialogue. Motivated by these improvements, we collected and distilled a diverse set of 2.6 million queries across multiple domains, using DeepSeek-R1-0528 as the teacher.
A notable… See the full description on the dataset page: https://huggingface.co/datasets/a-m-team/AM-DeepSeek-R1-0528-Distilled.Chinese-DeepSeek-R1-Distill-data-110k
中文基于满血DeepSeek-R1蒸馏数据集（Chinese-Data-Distill-From-R1）
🤗 Hugging Face | 🤖 ModelScope | 🚀 Github | 📑 Blog
注意：提供了直接SFT使用的版本，点击下载。将数据中的思考和答案整合成output字段，大部分SFT代码框架均可直接直接加载训练。
本数据集为中文开源蒸馏满血R1的数据集，数据集中不仅包含math数据，还包括大量的通用类型数据，总数量为110K。
为什么开源这个数据？
R1的效果十分强大，并且基于R1蒸馏数据SFT的小模型也展现出了强大的效果，但检索发现，大部分开源的R1蒸馏数据集均为英文数据集。 同时，R1的报告中展示，蒸馏模型中同时也使用了部分通用场景数据集。
为了帮助大家更好地复现R1蒸馏模型的效果，特此开源中文数据集。
该中文数据集中的数据分布如下：… See the full description on the dataset page: https://huggingface.co/datasets/Congliu/Chinese-DeepSeek-R1-Distill-data-110k.Chinese-DeepSeek-R1-Distill-data-110k-SFT
中文基于满血DeepSeek-R1蒸馏数据集（Chinese-Data-Distill-From-R1）
🤗 Hugging Face | 🤖 ModelScope | 🚀 Github | 📑 Blog
注意：该版本为，可以直接SFT使用的版本，将原始数据中的思考和答案整合成output字段，大部分SFT代码框架均可直接直接加载训练。
本数据集为中文开源蒸馏满血R1的数据集，数据集中不仅包含math数据，还包括大量的通用类型数据，总数量为110K。
为什么开源这个数据？
R1的效果十分强大，并且基于R1蒸馏数据SFT的小模型也展现出了强大的效果，但检索发现，大部分开源的R1蒸馏数据集均为英文数据集。 同时，R1的报告中展示，蒸馏模型中同时也使用了部分通用场景数据集。
为了帮助大家更好地复现R1蒸馏模型的效果，特此开源中文数据集。该中文数据集中的数据分布如下：
Math：共计36568个样本，
Exam：共计2432个样本，
STEM：共计12648个样本，… See the full description on the dataset page: https://huggingface.co/datasets/Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT.DeepSeek-R1-Distilled-Translate-en-zh_CN-39k
DeepSeek R1 满血蒸馏英中翻译数据集
本数据集是一个专门用于微调语言模型的英中翻译数据集，主要通过DeepSeek R1满血版蒸馏完成。
SFT训练版本
为了方便直接进行监督微调（Supervised Fine-tuning，SFT）训练，我们提供了两个使用标准 instruction-input-output 格式预的处理版本：
带 CoT 版本
保留了翻译过程中的思维链（Chain of Thought）
适合训练具有推理能力的翻译模型
无 CoT 版本
移除了思维链部分，只保留最终翻译结果
更适合训练直接输出翻译结果的模型
数据更简洁，训练更高效
项目依赖
本项目主要基于以下工具完成数据处理和生成：
llm-tools: 用于大语言模型数据处理的工具集合
qa-generator: 基于大语言模型的问答数据生成工具
数据集概览
关键统计
总样本数：38,981
数据集结构
字段说明… See the full description on the dataset page: https://huggingface.co/datasets/FradSer/DeepSeek-R1-Distilled-Translate-en-zh_CN-39k.DeepSeek-R1-Distilled-Translate-en-zh_CN-39k-Alpaca-GPT4
DeepSeek R1 满血蒸馏英中翻译数据集 Alpaca GPT-4（带 CoT 版本）
本数据集是 @FradSer/DeepSeek-R1-Distilled-Translate-en-zh_CN-39k 的 Alpaca GPT-4 版本，专门用于微调语言模型的英中翻译任务。采用标准的指令微调格式，更适合直接用于 SFT（Supervised Fine-tuning）训练。
本项目主要基于以下工具完成数据处理和生成：
llm-tools: 用于大语言模型数据处理的工具集合
数据集概览
关键统计
总样本数：38,981
数据集结构
字段说明
features:
- name: instruction # 待翻译的英文文本
dtype: string
- name: input # 空字符串，保持与标准指令格式一致
dtype: string
- name: output #… See the full description on the dataset page: https://huggingface.co/datasets/FradSer/DeepSeek-R1-Distilled-Translate-en-zh_CN-39k-Alpaca-GPT4.AM-DeepSeek-R1-Distilled-1.4MFor more open-source datasets, models, and methodologies, please visit our GitHub repository.
AM-DeepSeek-R1-Distilled-1.4M is a large-scale general reasoning task dataset composed of
high-quality and challenging reasoning problems. These problems are collected from numerous
open-source datasets, semantically deduplicated, and cleaned to eliminate test set contamination.
All responses in the dataset are distilled from the reasoning model (mostly DeepSeek-R1) and have undergone
rigorous… See the full description on the dataset page: https://huggingface.co/datasets/abcdefj123/AM-DeepSeek-R1-Distilled-1.4M.Raiden-DeepSeek-R1Click here to support our open-source dataset and model releases!
Raiden-DeepSeek-R1 is a dataset containing creative-reasoning and analytic-reasoning responses, testing the limits of DeepSeek R1's reasoning skills!
This dataset contains:
63k 'creative_content' and 'analytical_reasoning' prompts from microsoft/orca-agentinstruct-1M-v1, with all responses generated by deepseek-ai/DeepSeek-R1.
Responses demonstrate the reasoning capabilities of DeepSeek's 685b parameter R1 reasoning model.… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Raiden-DeepSeek-R1.AM-DeepSeek-R1-Filtered-Math-Code
AM DeepSeek R1 Filtered Math and Code
This repository publishes reproducible training subsets derived from
a-m-team/AM-DeepSeek-R1-Distilled-1.4M
at pinned revision 53531c06634904118a2dcd83961918c4d69d1cdf.
The source dataset and this derived release use CC BY-NC 4.0. Commercial use is
not permitted by that license. Preserve attribution and review the upstream
dataset card before use.
Contents
Config / split
Records
Bytes
SHA-256
math / train
111,657
2… See the full description on the dataset page: https://huggingface.co/datasets/chhao/AM-DeepSeek-R1-Filtered-Math-Code.DeepSeek-R1-Distill-Llama-8B-lmsys-openthoughts-tokenizedThis dataset is used for training Sparse Autoencoders (SAEs) to identify reasoning features in Large Language Models (LLMs), as described in the paper I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders.
Code for the paper is available at: https://github.com/AIRI-Institute/SAE-Reasoning
The dataset consists of tokenized text data used for training the SAEs.
dataset_info:
features:
name: tokens
sequence: int64
splits:
name:… See the full description on the dataset page: https://huggingface.co/datasets/andreuka18/DeepSeek-R1-Distill-Llama-8B-lmsys-openthoughts-tokenized.Math-Chinese-DeepSeek-R1-10K
中文 DeepSeek-R1-Distil 数学指令微调数据集
💻 Github Repo
基本信息
数据集大小 10K，独立生成指令与回复，并非其他社区数据集的子集。所有数据经过校验，答案正确性可以得到保证。
数据集的组成如下：
问题类型
数据条数
定积分计算
2626
多项式化简
1621
因式分解
2557
多项式展开
2095
多项式方程
1101
总数
10000
数据格式
每条数据的格式如下：
{
"id": <<12位nanoid>>,
"prompt": <<提示词>>,
"reasoning": <<模型思考过程>>,
"response": <<模型最终回复>>
}
Titanium2-DeepSeek-R1Click here to support our open-source dataset and model releases!
Titanium2-DeepSeek-R1 is a dataset focused on architecture and DevOps, testing the limits of DeepSeek R1's architect and coding skills!
This dataset contains:
32.4k synthetically generated prompts focused on architecture, cloud, and DevOps. All responses are generated using DeepSeek R1. Primary areas of expertise are architecture (problem solving, scenario analysis, coding, full SDLC) and DevOps (Azure, AWS, GCP, Terraform… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Titanium2-DeepSeek-R1.deepseek-r1-autonomous-math-logic-cot-2026
📐 Enterprise DeepSeek-R1 Autonomous Mathematical & Logic CoT SFT/DPO Dataset (2026)
High-precision multi-turn instruction tuning and preference optimization dataset with step-by-step hypothesis exploration, error discovery, and dynamic backtracking Chain-of-Thought (<thought>) reasoning trees for fine-tuning LLMs (DeepSeek-R1-Distill-Qwen, Qwen-2.5-Math, Llama-3.3, Mistral) into World-Class Olympiad Mathematicians and Formal Verification Agents.
📊 Dataset… See the full description on the dataset page: https://huggingface.co/datasets/beatsprom/deepseek-r1-autonomous-math-logic-cot-2026.DeepSeek-R1-Distilled-1.4MFor more open-source datasets, models, and methodologies, please visit our GitHub repository.
AM-DeepSeek-R1-Distilled-1.4M is a large-scale general reasoning task dataset composed of
high-quality and challenging reasoning problems. These problems are collected from numerous
open-source datasets, semantically deduplicated, and cleaned to eliminate test set contamination.
All responses in the dataset are distilled from the reasoning model (mostly DeepSeek-R1) and have undergone
rigorous… See the full description on the dataset page: https://huggingface.co/datasets/ibndias/DeepSeek-R1-Distilled-1.4M.Celestia3-DeepSeek-R1-0528Click here to support our open-source dataset and model releases!
Celestia3-DeepSeek-R1-0528 is a dataset focused on science, testing the limits of DeepSeek R1 0528's science-reasoning skills!
This dataset contains:
90.9k synthetically generated science prompts, with all responses generated using DeepSeek R1 0528.
Primary subjects are physics, chemistry, biology, and computer science; secondary subjects include Earth science, astronomy, and information theory.
All prompts are synthetic, taken… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Celestia3-DeepSeek-R1-0528.hwtcm-deepseek-r1-distill-data
简介
DeepSeek蒸馏的传统中医数据集，原始数据来源于网络，未进行人工审查。
7B模型微调效果
模型表现出了推理能力，准确性有待继续验证。
我们的其他产品
中医NER：能识别方剂、本草、来源、病名、症状、证型，也许是基于BERT开源模型中识别最好的模型。中医考试题：也许是全网最早开源、数据最多的中医考试题，我们内部将其用于模型训练的性能评测数据集。中医SFT数据集：中医QA数据集，用于SFT微调。仓公：基于Qwen的指令微调模型（暂未开源）。仓公R1：基于DeepSeek蒸馏的超过100万条QA的指令微调模型，拥有强大的推理能力（暂未开源）。
。。。还有很多
Citation
If you find this project useful in your research, please consider cite:
@misc{hwtcm2024,
title={{hwtcm-deepseek-r1-distill-data} A traditional… See the full description on the dataset page: https://huggingface.co/datasets/Monor/hwtcm-deepseek-r1-distill-data.DAG-Reasoning-DeepSeek-R1-0528Click here to support our open-source dataset and model releases!
DAG-Reasoning-DeepSeek-R1-0528 is a dataset focused on analysis and reasoning, creating directed acyclic graphs testing the limits of DeepSeek R1 0528's graph-reasoning skills!
This dataset contains:
4.08k synthetically generated prompts to create directed acyclic graphs in response to user input, with all responses generated using DeepSeek R1 0528.
All responses contain a multi-step thinking process to perform effective… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/DAG-Reasoning-DeepSeek-R1-0528.Chinese-DeepSeek-R1-Distill-data-110k-decontaminated
Decontaminated — Congliu/Chinese-DeepSeek-R1-Distill-data-110k
What this is
A filtered version of Congliu/Chinese-DeepSeek-R1-Distill-data-110k (revision
8520b649430617c2be4490f424d251d09d835ed3) with exact-duplicate rows and rows overlapping standard benchmark test sets
removed. This is a different artifact from the companion contamination report — that one is an
audit of what's wrong; this one is the corpus with those rows actually taken out, ready to train on.… See the full description on the dataset page: https://huggingface.co/datasets/liodon-ai/Chinese-DeepSeek-R1-Distill-data-110k-decontaminated.Titanium2.1-DeepSeek-R1Click here to support our open-source dataset and model releases!
Titanium2.1-DeepSeek-R1 is a dataset focused on architecture and DevOps, testing the limits of DeepSeek R1's architect and coding skills!
This dataset contains:
31.7k synthetically generated prompts focused on architecture, cloud, and DevOps. All responses are generated using DeepSeek R1. Primary areas of expertise are architecture (problem solving, scenario analysis, coding, full SDLC) and DevOps (Azure, AWS, GCP, Terraform… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Titanium2.1-DeepSeek-R1.Tachibana2-DeepSeek-R1-PREVIEWThis is a preview of the full Tachibana 2 high-difficulty code-reasoning dataset, containing the first ~6k rows. All responses generated by deepseek-ai/DeepSeek-R1.
The full dataset will be released for everyone once it's ready!
This dataset contains:
6k high-difficulty synthetic code-reasoning prompts created by Llama 3.1 405b Instruct, with an emphasis on task complexity and technical skill.
Responses demonstrate the reasoning capabilities of DeepSeek's 685b parameter R1 reasoning model.… See the full description on the dataset page: https://huggingface.co/datasets/sequelbox/Tachibana2-DeepSeek-R1-PREVIEW.dolphin-r1-korean-deepseek-parsed
[PARSED] dolphin R1 korean deepseek (toolcalls)
The data in this dataset is a subset of the original exp-models/dolphin-r1-korean-deepseek-toolcalls*Dropped row 1273 due to surrogates error.
Subset name
multi-turn
parallel
multiple definition
Last turn type
number of dataset
dolphin-r1-korean-deepseek
no
yes
yes
tool_calls
1757
dolphin-r1-korean-deepseek-non-reasoning
no
yes
yes
tool_calls
1757
This dataset is a re-parsed version of… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/dolphin-r1-korean-deepseek-parsed.Chinese-DeepSeek-R1-Distill-data-110k-contamination-report
Contamination Report — Congliu/Chinese-DeepSeek-R1-Distill-data-110k
What this is
A row-level audit of Congliu/Chinese-DeepSeek-R1-Distill-data-110k (revision
8520b649430617c2be4490f424d251d09d835ed3) for exact 13-gram overlap with standard benchmark test sets
(gsm8k, hellaswag, humaneval, mmlu). This is not a filtered copy of the source — it's a new
artifact: a list of which rows overlap which benchmark, plus summary statistics, so anyone
training on the source… See the full description on the dataset page: https://huggingface.co/datasets/liodon-ai/Chinese-DeepSeek-R1-Distill-data-110k-contamination-report.math500-cot-deepseek-r1-1.5b
MATH-500 CoT completions (DeepSeek-R1-Distill-Qwen-1.5B)
Successful chain-of-thought completions for HuggingFaceH4/MATH-500 test problems, generated with deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B via vLLM.
Files
File
Description
records.parquet
Main dataset: correct completions as token IDs
manifest.json
Schema, tokenizer, run ids, decoding config
problem_index.json
unique_id → problem_idx in MATH-500 test
subject_max_tokens.json
Per-subject completion… See the full description on the dataset page: https://huggingface.co/datasets/ChrisMcCormick/math500-cot-deepseek-r1-1.5b.Synthetic-Japanese-Roleplay-SFW-DeepSeek-R1-0528-10k
Synthetic-Japanese-Roleplay-SFW-DeepSeek-R1-0528-10k
概要
deepseek-ai/DeepSeek-R1-0528を用いて作成した、約10000件の日本語ロールプレイの対話を収録した合成データセットです。各データは20ターン程度あります。
データの詳細
各データは以下のキーを含んでいます。
major_genre: ジャンル（大分類）
minor_genre: ジャンル（小分類）
tag: 年齢制限用タグ（全年齢、R-15）
world_setting: 舞台・世界観の設定
scene_setting: 対話シーンの設定
user_setting: ユーザー側のキャラクターの設定
assistant_setting: アシスタント側のキャラクターの設定
dialogue_tone: 対話のトーン
conversations: 上記設定に基づいたユーザーとアシスタントの対話（OpenAI messages形式）
設定等の情報からsystem… See the full description on the dataset page: https://huggingface.co/datasets/Aratako/Synthetic-Japanese-Roleplay-SFW-DeepSeek-R1-0528-10k.Titanium2-DeepSeek-R1Click here to support our open-source dataset and model releases!
Titanium2-DeepSeek-R1 is a dataset focused on architecture and DevOps, testing the limits of DeepSeek R1's architect and coding skills!
This dataset contains:
32.4k synthetically generated prompts focused on architecture, cloud, and DevOps. All responses are generated using DeepSeek R1. Primary areas of expertise are architecture (problem solving, scenario analysis, coding, full SDLC) and DevOps (Azure, AWS, GCP, Terraform… See the full description on the dataset page: https://huggingface.co/datasets/gravermistakes/Titanium2-DeepSeek-R1.OpenThoughts-10k-DeepSeek-R1This repository contains the dataset used in the paper I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders.
Code: https://github.com/AIRI-Institute/SAE-Reasoning
deepseek-r1-systems-kernel-reasoning
🧠 DeepSeek-R1 Low-Level Systems & Kernel Reasoning Suite (2026)
🛒 Commercial Full Suite Available:
The full production suite with 10,000 SFT Hardware Reasoning Traces + 2,500 High-Contrast DPO Alignment Pairs across all 20 domains is available on Gumroad:
👉 Download Full Commercial Dataset on Gumroad (Starter \ / Pro \ / Enterprise )
A Tier-1 Commercial Dataset Suite engineered specifically for fine-tuning DeepSeek-R1, DeepSeek-R1-Distill-Qwen-14B/32B, and frontier… See the full description on the dataset page: https://huggingface.co/datasets/beatsprom/deepseek-r1-systems-kernel-reasoning.Synthetic-Japanese-Roleplay-SFW-DeepSeek-R1-0528-10k-formatted
Synthetic-Japanese-Roleplay-SFW-DeepSeek-R1-0528-10k-formatted
概要
deepseek-ai/DeepSeek-R1-0528を用いて作成した日本語ロールプレイデータセットであるAratako/Synthetic-Japanese-Roleplay-SFW-DeepSeek-R1-0528-10kにsystem messageを追加して整形したデータセットです。
データの詳細については元データセットのREADMEを参照してください。
ライセンス
MITライセンスの元配布します。
AM-DeepSeek-R1-Distilled-1.4MFor more open-source datasets, models, and methodologies, please visit our GitHub repository.
AM-DeepSeek-R1-Distilled-1.4M is a large-scale general reasoning task dataset composed of
high-quality and challenging reasoning problems. These problems are collected from numerous
open-source datasets, semantically deduplicated, and cleaned to eliminate test set contamination.
All responses in the dataset are distilled from the reasoning model (mostly DeepSeek-R1) and have undergone
rigorous… See the full description on the dataset page: https://huggingface.co/datasets/TOAO-Killer/AM-DeepSeek-R1-Distilled-1.4M.Synthetic-Japanese-Roleplay-NSFW-DeepSeek-R1-0528-10k
Synthetic-Japanese-Roleplay-NSFW-DeepSeek-R1-0528-10k
概要
deepseek-ai/DeepSeek-R1-0528を用いて作成した、約10000件の日本語ロールプレイの対話を収録した合成データセットです。各データは20ターン程度あります。
このデータセットはNSFW表現を含みます。
データの詳細
各データは以下のキーを含んでいます。
major_genre: ジャンル（大分類）
minor_genre: ジャンル（小分類）
tag: 年齢制限用タグ（R-18）
world_setting: 舞台・世界観の設定
scene_setting: 対話シーンの設定
user_setting: ユーザー側のキャラクターの設定
assistant_setting: アシスタント側のキャラクターの設定
dialogue_tone: 対話のトーン
conversations: 上記設定に基づいたユーザーとアシスタントの対話（OpenAI messages形式）… See the full description on the dataset page: https://huggingface.co/datasets/Aratako/Synthetic-Japanese-Roleplay-NSFW-DeepSeek-R1-0528-10k.