datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.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.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.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.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。
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.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.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.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-Distill-Bangla-MMLU-Reasoning-DataDeepSeek R1 Bangla MMLU Distil Dataset
Original Dataset: hishab/bangla-mmlu
Train Samples: 17,796
Test Samples: 2,576
Total API Cost: 7K BDT
Contributors:
Myself
Numaer
How the Dataset was created
Step 1 - Base Dataset
I've used bangla-mmlu dataset released by hisab. Kudos to them for creating and open sourcing the dataset. Without their dataset this synthetic reasoning dataset won't exist in the first place.
Step 2 - Select Subset
Since I'm… See the full description on the dataset page: https://huggingface.co/datasets/KillerShoaib/DeepSeek-r1-Distill-Bangla-MMLU-Reasoning-Data.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.Synthetic-Japanese-Roleplay-NSFW-DeepSeek-R1-0528-10k-formatted
Synthetic-Japanese-Roleplay-NSFW-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-NSFW-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。
local-code-arena-deepseek-r1_1.5b
Local Code Arena Telemetry: MBPP Benchmark on DeepSeek R1 1.5B
This repository hosts the raw evaluation metrics, execution telemetry logs, and structural syntax outputs captured from running the Mostly Basic Python Problems (MBPP) benchmark against the DeepSeek R1 1.5B distilled reasoning architecture.
This specific run establishes the performance boundaries of lightweight reasoning models under strict execution time limits on consumer hardware.
📊 Core Performance… See the full description on the dataset page: https://huggingface.co/datasets/ShahzebKhoso/local-code-arena-deepseek-r1_1.5b.DeepSeek-R1-Distill-Llama-8B-MATH-traces
DeepSeek-R1-Distill-Llama-8B MATH Reasoning Traces
10,000 reasoning traces from DeepSeek-R1-Distill-Llama-8B on MATH problems.
Model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B (served via vLLM)
Source problems: xDAN2099/lighteval-MATH (train split)
Sampling: 500 problems (100 per difficulty level 1-5) x 20 rollouts
Generation params: temperature=0.6, top_p=0.95, max_tokens=15000
Accuracy: 80.1% (8,008 correct / 1,992 incorrect)
Problem types: Algebra, Counting & Probability… See the full description on the dataset page: https://huggingface.co/datasets/jrosseruk/DeepSeek-R1-Distill-Llama-8B-MATH-traces.Chinese-DeepSeek-R1-Distill-data-110k-opencc
中文基於滿血DeepSeek-R1蒸餾數據集（Chinese-Data-Distill-From-R1）
🤗 Hugging Face | 🤖 ModelScope | 🚀 Github | 📑 Blog
本資料集由 Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT 經過 opencc 轉換而成，再次感謝原作者。
注意：該版本為，可以直接SFT使用的版本，將原始數據中的思考和答案整合成output字段，大部分SFT代碼框架均可直接直接加載訓練。
本數據集為中文開源蒸餾滿血R1的數據集，數據集中不僅包含math數據，還包括大量的通用類型數據，總數量為110K。
為什麽開源這個數據？
R1的效果十分強大，並且基於R1蒸餾數據SFT的小模型也展現出了強大的效果，但檢索發現，大部分開源的R1蒸餾數據集均為英文數據集。 同時，R1的報告中展示，蒸餾模型中同時也使用了部分通用場景數據集。
為了幫助大家更好地覆現R1蒸餾模型的效果，特此開源中文數據集。… See the full description on the dataset page: https://huggingface.co/datasets/benchang1110/Chinese-DeepSeek-R1-Distill-data-110k-opencc.DeepSeek-R1-Distill-Llama-8B-MATH-labeled-sentences
DeepSeek-R1-Distill-Llama-8B MATH Labeled Sentences
Sentence-level function-tag labels for reasoning traces from DeepSeek-R1-Distill-Llama-8B on MATH problems.
Trace model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B (served via vLLM)
Label model: gpt-4o-mini
Source traces: jrosseruk/DeepSeek-R1-Distill-Llama-8B-MATH-traces-balanced
Total sentences: 435,525
Backtrack sentences: 39,998 (9.2%)
Traces: 4,413 (2,496 correct, 1,917 incorrect)
Each sentence in a chain-of-thought trace is… See the full description on the dataset page: https://huggingface.co/datasets/jrosseruk/DeepSeek-R1-Distill-Llama-8B-MATH-labeled-sentences.local-code-arena-eval_results_deepseek-r1_8b
Local Code Arena Telemetry: MBPP Benchmark on DeepSeek R1 8B
This repository hosts the raw evaluation metrics, execution telemetry logs, and structural syntax outputs captured from running the Mostly Basic Python Problems (MBPP) benchmark against the DeepSeek R1 8B distilled reasoning architecture.
This specific run establishes the operational baseline and performance characteristics of mid-tier reasoning models under strict automated evaluation and sandbox time limits on… See the full description on the dataset page: https://huggingface.co/datasets/ShahzebKhoso/local-code-arena-eval_results_deepseek-r1_8b.math500-deepseek-r1-distill-qwen-14b
Dataset Card for "math500-deepseek-r1-distill-qwen-14b"
Dataset Summary
This dataset is a distilled version of the MATH500 dataset, augmented with reasoning-based responses generated by the deepseek-r1-distill-qwen-14b language model. The dataset is designed to evaluate and improve the mathematical reasoning capabilities of LLMs through step-by-step solutions and final answers.
Each example consists of:
The original problem statement from MATH500
The reference solution… See the full description on the dataset page: https://huggingface.co/datasets/jsm0424/math500-deepseek-r1-distill-qwen-14b.math500-deepseek-r1-distill-qwen-1.5b
Dataset Card for "math500-deepseek-r1-distill-qwen-1.5b"
Dataset Summary
This dataset is a distilled version of the MATH500 dataset, augmented with reasoning-based responses generated by the deepseek-r1-distill-qwen-1.5b language model. The dataset is designed to evaluate and improve the mathematical reasoning capabilities of LLMs through step-by-step solutions and final answers.
Each example consists of:
The original problem statement from MATH500
The reference solution… See the full description on the dataset page: https://huggingface.co/datasets/jsm0424/math500-deepseek-r1-distill-qwen-1.5b.DeepSeek-R1-Distill-Llama-8B-MATH-traces-balanced
DeepSeek-R1-Distill-Llama-8B MATH Reasoning Traces (Balanced)
4,492 reasoning traces from DeepSeek-R1-Distill-Llama-8B on MATH problems, balanced for correct/incorrect.
Model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B (served via vLLM)
Source problems: xDAN2099/lighteval-MATH (train split)
Sampling: Subsampled from the full 10k trace set — 2,500 correct + 1,992 incorrect (all available incorrect traces)
Generation params: temperature=0.6, top_p=0.95, max_tokens=15000
Accuracy: 55.7%… See the full description on the dataset page: https://huggingface.co/datasets/jrosseruk/DeepSeek-R1-Distill-Llama-8B-MATH-traces-balanced.Claude-Deepseek-R1-Combined_ru
SuperbEmphasis/Claude-Deepseek-R1-Combined (Russian Translation)
🌐 Переведённый датасет для ролевых диалоговЭто русскоязычная версия датасета Claude-Deepseek-R1-Combined, содержащая диалоги в формате ролевых чатов.
Структура данных
Каждый элемент — список сообщений формата:
[
{
"idx": 0,
"role": "system", # или "user", "assistant"
"content": "Русский перевод...",
"en_content": "Original English text..."
},
...
]
⚠️ Отказ от… See the full description on the dataset page: https://huggingface.co/datasets/Arketov/Claude-Deepseek-R1-Combined_ru.