datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DeepSeek-v4-Pro-AgentThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
DeepSeek v4 Pro Agent Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by deepseek/deepseek-v4-pro.
JSONL files: 4006
Training-ready tools
A complete configured tools schema snapshot is embedded in the collapsed section at the bottom of… See the full description on the dataset page: https://huggingface.co/datasets/TeichAI/DeepSeek-v4-Pro-Agent.AM-DeepSeek-Distilled-40MFor more open-source datasets, models, and methodologies, please visit our GitHub repository and paper: DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training.
Due to certain constraints, we are only able to open-source a subset of the complete dataset.
Model Training Performance based on our complete dataset
On AIME 2024, our 72B model achieved a score of 79.2 using only supervised fine-tuning (SFT). The 32B model reached 75.8 and… See the full description on the dataset page: https://huggingface.co/datasets/a-m-team/AM-DeepSeek-Distilled-40M.ArXivSignals-DeepSummaries
ArXivSignals DeepSummaries — Agent-Built Visual Paper Explainers
A continuously-updated, day-partitioned dataset of deep, visual summaries of
arXiv papers, each built by a coding agent working inside the paper's own
LaTeX source: the agent reads the full text, authors an editorial narrative as
a structured content spec, and the paper's real figures and tables
(extracted and rendered from the LaTeX, web-optimized) ride along as an
embedded, variable-length image array. The… See the full description on the dataset page: https://huggingface.co/datasets/taesiri/ArXivSignals-DeepSummaries.deepseek-v4-pro-0813-agentic
DeepSeek-V4-Pro 0813 Agentic (DS4)
A standalone, verifiable-first agentic training corpus: 19,072 training traces
plus 2,135 held-out evaluation rows (validation 1,070 / test 1,065), generated by
DeepSeek-V4-Pro 0813 (deepseek-v4-pro-0813, official API, thinking mode) across 13 verifiable task families,
each row admitted only after passing a deterministic programmatic verifier. The corpus is
designed to be directly usable for SFT, GRPO/RLVR, and NeMo Gym / NeMo RL
(verified… See the full description on the dataset page: https://huggingface.co/datasets/r0b0tlab/deepseek-v4-pro-0813-agentic.DeepSeek-v4-Pro-AgentThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
DeepSeek v4 Pro Agent Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by deepseek/deepseek-v4-pro.
JSONL files: 4006
Training-ready tools
A complete configured tools schema snapshot is embedded in the collapsed section at the bottom of… See the full description on the dataset page: https://huggingface.co/datasets/ronaldcmz/DeepSeek-v4-Pro-Agent.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.saas-sales-conversations
saas-sales-conversations
Dataset Description
This is a synthetic dataset of sales conversations for SaaS (Software as a Service) companies, designed for training sales conversion prediction models. The dataset was created following the methodology presented in "SalesRLAgent: A Reinforcement Learning Approach for Real-Time Sales Conversion Prediction and Optimization" (Nandakishor M, 2025).
The dataset contains realistic dialogues between sales representatives and… See the full description on the dataset page: https://huggingface.co/datasets/DeepMostInnovations/saas-sales-conversations.DeepSeek-v4-Pro-AgentThis dataset was generated using teich by TeichAI
Prepare these datasets for supervised fine-tuning in just a few lines of code — see the Conversion section below.
DeepSeek v4 Pro Agent Traces
This directory contains raw agent trace files generated by teich.
All assistant responses were generated by deepseek/deepseek-v4-pro.
JSONL files: 4006
Training-ready tools
A complete configured tools schema snapshot is embedded in the collapsed section at the bottom of… See the full description on the dataset page: https://huggingface.co/datasets/hardcoremoore/DeepSeek-v4-Pro-Agent.cc100_char_freq
Letter Frequency Table on CC-110
This is the letter frequency analysis table based on CC-110 dataset.
116 languages supported, 50882 letters supported in total.
This dataset is useful for do some basic checking, e.g. by calculating the weighted sum, the proportion of daily-used characters in a certain language that a font file can support can be checked to determine whether it truly supports a certain language.
deepseek-hermes-reasoning-traces
DeepSeek V4 Pro Hermes Reasoning Traces
19,331 multi-turn ChatML + Hermes reasoning traces generated by DeepSeek V4 Pro. Designed for LoRA fine-tuning local models to operate as Hermes Agent instances.
Quick Start
\
Splits
Split
Traces
train
16,431
valid
1,933
test
967
Variants (VRAM-Tiered)
Variant
Max Tokens
Traces
GPU
nano
2,048
15,948
Dev / 7B
budget
4,096
2,149
48GB
standard
8,192
990
64GB
spark
16,384
244… See the full description on the dataset page: https://huggingface.co/datasets/r0b0tlab/deepseek-hermes-reasoning-traces.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.DeepTheorem
DeepTheorem: Advancing LLM Reasoning for Theorem Proving Through Natural Language and Reinforcement Learning 🚀
Welcome to the GitHub repository for DeepTheorem 🎉, a comprehensive framework for enhancing large language model (LLM) mathematical reasoning through informal, natural language-based theorem proving. This project introduces a novel approach to automated theorem proving (ATP) by leveraging the informal reasoning strengths of LLMs, moving beyond traditional formal proof… See the full description on the dataset page: https://huggingface.co/datasets/Jiahao004/DeepTheorem.openresearcher-sft-deep-research-cleaned
OpenResearcher SFT DeepResearch — Parquet Mirror
This is a re-hosted copy of the tool-reasoning SFT deep-research dataset by Aman Priyanshu, itself a cleaned/restructured version of the OpenResearcher Dataset from TIGER-AI-Lab.
Why this repo exists: the source wasn't laid out as ready-to-download Parquet files. This mirror simply stores the data as plain seed_*.parquet files so you can grab the whole dataset or a single segment easily. No changes were made to the content — all… See the full description on the dataset page: https://huggingface.co/datasets/DanielTobi0/openresearcher-sft-deep-research-cleaned.DeepResearch-traj
DeepResearch-traj
Multi-seed deep research agent trajectories with per-question correctness labels and pass@k statistics, derived from OpenResearcher/OpenResearcher-Dataset.
Dataset Summary
This dataset contains 97,630 full agent trajectories across 6,102 unique research questions, each sampled under 16 different random seeds (42–57). Every trajectory is annotated with:
seed — which random seed produced this trajectory
correct — whether the model's final answer was… See the full description on the dataset page: https://huggingface.co/datasets/IPF/DeepResearch-traj.arxiv_deep_learning_python_research_code
ArXiv Deep Learning Python Research Code
A curated corpus of Python source code files extracted from GitHub repositories referenced in ArXiv papers. Contains 391,496 files (1.49 GB) filtered to deep learning frameworks, designed for training and evaluating Code LLMs on research-grade code.
Dataset Summary
Statistic
Value
Total files
391,496
Total size
1.49 GB
Source repos
34,099
Time span
ArXiv inception through July 2023
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_deep_learning_python_research_code.deepresearchgym-agentic-search-logs
DeepResearchGym Agentic Search Logs
This repository hosts the dataset accompanying the paper “Agentic Search in the Wild” (arXiv: https://arxiv.org/abs/2601.17617).
The dataset contains 14M+ search queries collected via DeepResearchGym (DRGym), an open-source search API designed for DeepResearch-style agentic search. For more background on DRGym, see: https://arxiv.org/abs/2505.19253.
All records have been anonymized and shuffled to prevent re-identification, and we additionally… See the full description on the dataset page: https://huggingface.co/datasets/cx-cmu/deepresearchgym-agentic-search-logs.deepseek-v4-tiny-cpu-repro-v1
DeepSeek-V4 tiny corrected-native-primitives CPU text fixture
Complete randomly initialized, untrained QFSDeepseekV4ForCausalLM text class
using Transformers5.16.1 native primitives and a reviewed RMSNorm arithmetic correction.
No upstream weights, paid GPU/cloud compute or useful-model claim.
This is not unmodified native Transformers or the complete production release.
Architecture and scope
Text lineage:… See the full description on the dataset page: https://huggingface.co/datasets/malaiwah/deepseek-v4-tiny-cpu-repro-v1.DeepSeek-V4-Flash-0731-Teacher-Distillation-40513x
DeepSeek V4 Flash 0731 Teacher Distillation — 40,513 Retained Rows
Teacher-distillation corpus generated with
deepseek-ai/DeepSeek-V4-Flash-0731.
The original manifest contained 45,000 unique seeds.
Following generation, QC, retry-based repair, quarantine auditing,
and recovery adjudication, 40,513 rows were retained.
Composition
Bucket
Rows
Coding
5,601
Agentic
9,982
Cyber blue
13,000
Controlled cyber red
6,999
Tool use
4,931
Total
40,513… See the full description on the dataset page: https://huggingface.co/datasets/trjxter/DeepSeek-V4-Flash-0731-Teacher-Distillation-40513x.scale-swe-distill5000-deepseek-v4-flash-0731-think-rollout4-instance3393-trajectories7928
Scale-SWE DeepSeek V4 Flash 0731 Think Rollouts
Successful AweAgent trajectories generated with deepseek-v4-flash-0731 in think mode.
Dataset summary
Source task instances: 3,393
Rollouts per source instance: 4
Total attempted rollouts: 13,572
Successful exported trajectories: 7,928
Unique instances represented by successful trajectories: 2,250
Scaffold: aweagent
Tool-call format: openai_function
The export retains assistant reasoning_content, function tool… See the full description on the dataset page: https://huggingface.co/datasets/wjn922-01/scale-swe-distill5000-deepseek-v4-flash-0731-think-rollout4-instance3393-trajectories7928.deepagent
DeepAgent
Hard, Docker-verifiable software-engineering benchmarks from real merged PRs
DeepAgent ships real_pr Harbor hardness packs: live-mined multi-file pull requests, clone@SHA agent images, held-out verifier tests, and Docker dual-truth (solution reward = 1, null reward = 0). Primary product work runs through the deepagent CLI in the GitHub monorepo.
Surface
Ref
Role
HF stable pin
this dataset revision main
Current product on Hub (N=9)
HF automation… See the full description on the dataset page: https://huggingface.co/datasets/BaseIntelligence/deepagent.Deepseek-V4-Reasoning-Code-2500
DeepSeek Reasoning and Code Distillation Dataset
This dataset contains synthetic instruction-response examples generated from coding, reasoning, and math prompts. It was generated with enforce_distillable_text enabled using DeepSeek V4 Pro and DeepSeek V4 Flash through OpenRouter. It is intended for experimentation with supervised fine-tuning, response-style distillation, reasoning-format analysis, and code-assistant behavior research.
The dataset file is:
train.csv
It contains 2… See the full description on the dataset page: https://huggingface.co/datasets/Banaxi-Tech/Deepseek-V4-Reasoning-Code-2500.swebench-verified-deepseek-v4-flash-failure-analysis
SWE-bench Verified runs & failure analysis — DeepSeek-V4-flash (local) × mini-swe-agent
Per-instance analysis of SWE-bench Verified runs of a locally-served DeepSeek-V4-flash model
driven by mini-swe-agent, graded with the official
SWE-bench harness. Each instance carries the full agent trajectory, a readable transcript, the
submitted patch, the harness test output, deterministic metrics, and a hand-verified qualitative
root-cause diagnosis.
Current numbers (resolve rates… See the full description on the dataset page: https://huggingface.co/datasets/daaain/swebench-verified-deepseek-v4-flash-failure-analysis.CodeGen-Deep-5K
CodeGen-Deep-5K: Deep Reasoning for Competitive Programming
Part of the CodeGen suite | CodeGen-Diverse-5K (sister dataset)
Dataset Description
CodeGen-Deep-5K is a deep reasoning dataset designed for training code generation models with enhanced problem-solving capabilities. Unlike traditional datasets, this generates multiple distinct solutions for each problem, providing varied reasoning traces and approaches.
Key Statistics
Total samples: 5,000
Unique… See the full description on the dataset page: https://huggingface.co/datasets/Naholav/CodeGen-Deep-5K.pi-publish
Coding agent session traces for deepflame-bot/pi-publish
This dataset contains redacted coding agent session traces collected while working on https://github.com/xke-b/efno-chem-kinetics.git. The traces were exported with pi-share-hf from a local pi workspace and filtered to keep only sessions that passed deterministic redaction and LLM review.
Data description
Each *.jsonl file is a redacted pi session. Sessions are stored as JSON Lines files where each line is a… See the full description on the dataset page: https://huggingface.co/datasets/deepflame-bot/pi-publish.deepseek-v4-pro-0813-agentic
DeepSeek-V4-Pro 0813 Agentic (DS4)
A standalone, verifiable-first agentic training corpus: 19,072 training traces
plus 2,135 held-out evaluation rows (validation 1,070 / test 1,065), generated by
DeepSeek-V4-Pro 0813 (deepseek-v4-pro-0813, official API, thinking mode) across 13 verifiable task families,
each row admitted only after passing a deterministic programmatic verifier. The corpus is
designed to be directly usable for SFT, GRPO/RLVR, and NeMo Gym / NeMo RL
(verified… See the full description on the dataset page: https://huggingface.co/datasets/ArkhAngelLifeJiggy/deepseek-v4-pro-0813-agentic.deepseek-v4-pro-math-cot-1k
DeepSeek V4 Pro Math CoT 1K
A small, high-signal supervised-fine-tuning (SFT) dataset of math reasoning traces. Problems were sampled from a Nemotron math problem set (originally sourced from StackExchange-Math and AoPS), answered by DeepSeek V4 Pro with thinking enabled at high reasoning effort, then independently reviewed by DeepSeek V4 Flash for correctness against the expected answer. Pathological reasoning traces (looping, run-away length, excessive Wait-style backtracking)… See the full description on the dataset page: https://huggingface.co/datasets/blythet/deepseek-v4-pro-math-cot-1k.Qwen3.5-27B-DeepCoder-SFT
Overview
This dataset contains 14,683 verified code solutions with chain-of-thought reasoning, generated by Qwen3.5-27B on competitive programming problems. Each example has been executed against test cases in a sandboxed environment and passes 100% of tests.
Key features:
Reasoning traces — 77.5% of examples include step-by-step reasoning before the final code solution
Verified correctness — every solution passes all test cases (up to 30 per problem)
Rejection sampled — 8… See the full description on the dataset page: https://huggingface.co/datasets/zake7749/Qwen3.5-27B-DeepCoder-SFT.tool-reasoning-sft-RESEARCH-dr-tulu-sft-deep-research-agent-data-cleaned-rectified
Deep Research - Tulu SFT Data Cleaned Rectified
👥 Follow the Author
Supriti Vijay
Overview
This dataset is a cleaned and restructured version of the DR-TULU SFT dataset released by AllenAI's RL Research team. The original DR-TULU dataset represents significant work in creating high-quality training data for reasoning-enhanced language models with tool use capabilities. This version addresses structural issues in the original release while preserving… See the full description on the dataset page: https://huggingface.co/datasets/SupritiVijay/tool-reasoning-sft-RESEARCH-dr-tulu-sft-deep-research-agent-data-cleaned-rectified.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.deep-space-optical-chip-thermal-dataset
🚀 Deep Space Optical Chip Thermal Dataset 🪐
🌡️ 40,000 scenario-based prompt and response pairs on thermal mitigation for photonic chips in scientific instruments aboard deep-space probes, covering refractive index drift, waveguide misalignment, and thermal stress across materials, instruments, and environments.
⚠️ Disclaimer: All entries are synthetically generated. Material coefficients are drawn from published typical values, but no row is based on mission logs or flight… See the full description on the dataset page: https://huggingface.co/datasets/Taylor658/deep-space-optical-chip-thermal-dataset.