datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
po_qwen14b_tabular_data
BoLT Prompt Optimization — Tabular Dataset
For prompt optimization tasks in BoLT, an accessible benchmark for black-box optimization on LLM tasks.
Dataset Description
The dataset covers 5,014 evaluated instructions. Each row is a candidate system-prompt instruction paired with its empirically measured MATH-500 (4-shot, non-thinking mode) scores.
Evaluation details:
Model: Qwen/Qwen3-14B
Task: minerva_math500 (4-shot) (from lm-eval library)
System prompt:… See the full description on the dataset page: https://huggingface.co/datasets/chewwt/po_qwen14b_tabular_data.helaxai_data_pluse
🥞 The Stack v3
What is it?
What is being released
How to download and use it
Dataset statistics
Dataset structure
Dataset creation
Considerations for using the data
Additional information
What is it?
The Stack v3 is the largest, most up-to-date open dataset of source code, crawled directly from GitHub and built to pre-train code LLMs with full-repository context. It is the successor to The Stack v2 and, like its predecessor, is released to make the training… See the full description on the dataset page: https://huggingface.co/datasets/nhblk123/helaxai_data_pluse.car-bench-dataset
CAR-Bench Dataset
CAR-Bench is a benchmark for evaluating AI voice assistants in a realistic automotive (car) environment.
It tests an agent's ability to correctly use vehicle control tools, handle disambiguation, and avoid hallucinations.
Dataset Structure
The dataset is organized into task configs and mock data configs:
Tasks
Each task defines a user persona, an instruction, the initial vehicle/environment context, and the ground-truth sequence of tool-call… See the full description on the dataset page: https://huggingface.co/datasets/johanneskirmayr/car-bench-dataset.Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection
🧬 Omni-Frontier Collection
Cybersecurity · Coding · Math · Science · RSI Reasoning — one unified SFT package
A unified, deduplicated, fully-browsable distillation & SFT corpus — every row real, every row visible.
📖 Jump to
What's inside · 🔁 Aggregation audit · 🛡 Cybersecurity · 💻 Coding · 🏭 Distillation deep-dive · 🔁 RSI · 🧮 Math/Science/More · 🎓 Training guide · 🔎 Browsing · 🧹 Quality · 🗺 Roadmap · 📄 License… See the full description on the dataset page: https://huggingface.co/datasets/SHSLab/Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection.dataset-the-stack-v2-dedup-sub
The Stack v2 Subset with File Contents (Python, Java, JavaScript, C, C++)
TempestTeam/dataset-the-stack-v2-dedup-sub
Dataset Summary
This dataset is a language-filtered and self-contained subset of bigcode/the-stack-v2-dedup, part
of the BigCode Project.
It contains only files written in the following programming languages:
Python 🐍
Java ☕
JavaScript 📜
C ⚙️
C++ ⚙️
Unlike the original dataset, which only includes metadata and Software Heritage IDs, this subset includes… See the full description on the dataset page: https://huggingface.co/datasets/Cyrile/dataset-the-stack-v2-dedup-sub.YuLan-Mini-Text-Datasets
News
[2025.04.11] Add dataset mixture: link.
[2025.03.30] Text datasets upload finished.
This is text dataset.
这是文本格式的数据集。
Since we have used BPE-Dropout, in order to ensure accuracy, you can find the tokenized dataset here.
由于我们使用了BPE-Dropout，为了保证准确性，你可以在这里找到分词后的数据。
For more information, please refer to our datasets details and preprocess details.
Contributing
We welcome any form of contribution, including feedback on model bad cases, feature suggestions, and example… See the full description on the dataset page: https://huggingface.co/datasets/yulan-team/YuLan-Mini-Text-Datasets.monoweb-dataset
MonoWeb Dataset
MonoWeb is a multilingual pretraining corpus derived from FineWeb-Edu (English) and FineWeb2 (German, Spanish, French) by systematically removing all mixed-language documents.
Released alongside the paper:
The Role of Mixed-Language Documents for Multilingual Large Language Model Pretraining
Dataset Structure
monoweb-dataset/
├── eng/ # Full English corpus (FineWeb-Edu)
├── deu/… See the full description on the dataset page: https://huggingface.co/datasets/UCLNLP/monoweb-dataset.nuclear-intelligence-dataset
Nuclear Intelligence Dataset
Public, auto-generated dataset of validated nuclear-energy research cycles.
Latest stats (auto-updated):
🪙 NES tokens minted: 0
⛓️ Blockchain length: 1 blocks
🕸️ Knowledge entities: 2
Source
GitHub: https://github.com/QalamHipHop/nuclear-intelligence
HF Space: https://huggingface.co/spaces/Qalam/Nuclear-Intelligence
License
MIT
moltbook-dataset
Moltbook Dataset
A longitudinal dataset of social interactions from Moltbook — an AI-agent social platform where autonomous "Molties" post, comment, and interact. Collected automatically and published as timestamped snapshots for temporal analysis.
Dataset Statistics
Metric
Count
Posts (platform total)
--
Comments (platform total)
2,125,205
Posts (collected)
25,895
Comments (collected)
275,867
Agents
5,859
Social graph edges
16,990
Reply… See the full description on the dataset page: https://huggingface.co/datasets/takschdube/moltbook-dataset.Mixed-Arabic-Datasets-Repo
Dataset Card for "Mixed Arabic Datasets (MAD) Corpus"
The Mixed Arabic Datasets Corpus : A Community-Driven Collection of Diverse Arabic Texts
Dataset Description
The Mixed Arabic Datasets (MAD) presents a dynamic compilation of diverse Arabic texts sourced from various online platforms and datasets. It addresses a critical challenge faced by researchers, linguists, and language enthusiasts: the fragmentation of Arabic language datasets across the Internet. With MAD, we… See the full description on the dataset page: https://huggingface.co/datasets/M-A-D/Mixed-Arabic-Datasets-Repo.pretrain_data_eukaryote
GENERator-v2-Eukaryote Gene-Centric Pretraining Corpus
This repository provides the gene-centric pretraining corpus underlying GENERator-v2-Eukaryote, a large-scale DNA language model for eukaryotic genome understanding.
The dataset is constructed by leveraging RefSeq annotations to extract biologically meaningful functional genomic regions, which serve as the foundation for large-context DNA language model pretraining.
📌 Dataset Construction Overview
The core… See the full description on the dataset page: https://huggingface.co/datasets/GenerTeam/pretrain_data_eukaryote.10k_prompts_ranked
Dataset Card for 10k_prompts_ranked
10k_prompts_ranked is a dataset of prompts with quality rankings created by 314 members of the open-source ML community using Argilla, an open-source tool to label data. The prompts in this dataset include both synthetic and human-generated prompts sourced from a variety of heavily used datasets that include prompts.
The dataset contains 10,331 examples and can be used for training and evaluating language models on prompt ranking tasks. The… See the full description on the dataset page: https://huggingface.co/datasets/data-is-better-together/10k_prompts_ranked.task_data
QuantCodeEval
A benchmark for evaluating LLM coding agents on quantitative-strategy code
reproduction from finance research papers.
Status: Anonymous artifact for the 30-task benchmark.
Release mirrors
The release is mirrored at two anonymous locations:
Hugging Face Datasets — complete anonymous release:
https://huggingface.co/datasets/quantcodeeval/task_data
anonymous.4open.science — browseable mirror:
https://anonymous.4open.science/r/QuantCodeEval-Anonymous… See the full description on the dataset page: https://huggingface.co/datasets/quantcodeeval/task_data.Open-MOPD-Data
Open-MOPD Data
This repository contains the training and evaluation data released with
Open-MOPD, including mixed-domain supervised fine-tuning data, the shared
RL/OPD prompt mixture, and six evaluation benchmarks.
Dataset contents
Configuration
Description
Examples
rl_prompt_mix
Shared math, code, and instruction-following prompts for RL and OPD
86,931
sft_openr1_math_93k
Math SFT data in a unified think-tag format
93,733
sft_ocr_50k
Sampled… See the full description on the dataset page: https://huggingface.co/datasets/BytedTsinghua-SIA/Open-MOPD-Data.tts-datagen
GPT-OSS 120B native reasoning traces for TTS Datagen
Summary
This dataset contains 2,865 synthetic competitive-programming questions,
45,840 independently sampled GPT-OSS 120B solutions (16 per question), and 50
verified test cases per question (143,250 test cases total). Each solution
preserves the model's native reasoning trace separately from its final answer.
The reasoning was returned by MetaGen's native Dialog Completion interface as
dialog reasoning… See the full description on the dataset page: https://huggingface.co/datasets/harman/tts-datagen.Salad-Data
Data Description
✊ How to use
from datasets import load_dataset
dataset = load_dataset("OpenSafetyLab/Salad-Data", name='base_set', split='train')
📊 Statistical Overview of Base Question
Type
Data Source
Nums
Self-instructed
Finetuned GPT-3.5
15,433
Open-Sourced
HH-harmless
4,184
HH-red-team
659
Advbench
359
Multilingual
230
Do-Not-Answer
189
ToxicChat
129
Do Anything Now
93
GPTFuzzer
42
Total
21,318… See the full description on the dataset page: https://huggingface.co/datasets/OpenSafetyLab/Salad-Data.wiki_snippets
Dataset Card for "wiki_snippets"
Dataset Summary
Wikipedia version split into plain text snippets for dense semantic indexing.
Supported Tasks and Leaderboards
More Information Needed
Languages
More Information Needed
Dataset Structure
We show detailed information for 2 configurations of the dataset (with 100 snippet passage length and 0 overlap) in
English:
wiki40b_en_100_0: Wiki-40B
wikipedia_en_100_0: Wikipedia
Data Instances… See the full description on the dataset page: https://huggingface.co/datasets/community-datasets/wiki_snippets.dr-saeid-ghezelbaash-entity-data
Dr. Saeed Ghezelbash Public Knowledge Graph
A public, physician-authored knowledge graph and multilingual retrieval dataset by Dr. Saeed Ghezelbash, a physician in Kermanshah, Iran. It connects physician identity, aesthetic medicine services, published question-answer content and cited evidence for entity resolution and evidence-grounded AI retrieval.
The canonical source is the official website and Dataset graph. This Hugging Face repository is its AI distribution. The… See the full description on the dataset page: https://huggingface.co/datasets/doctor-ghezelbaash/dr-saeid-ghezelbaash-entity-data.code_contests_instruct
Dataset Card for "code_contests_instruct"
The deepmind/code_contests dataset formatted as markdown-instruct for text generation training.
There are several different configs. Look at them. Comments:
flesch_reading_ease is computed on the description col via textstat
hq means that python2 (aka PYTHON in language column) is dropped, and keeps only rows with flesch_reading_ease 75 or greater
min-cols drops all cols except language and text
possible values for language are {'CPP'… See the full description on the dataset page: https://huggingface.co/datasets/BEE-spoke-data/code_contests_instruct.glucose
Dataset Card for [Dataset Name]
Dataset Summary
GLUCOSE: GeneraLized and COntextualized Story Explanations, is a novel conceptual framework and dataset for commonsense reasoning. Given a short story and a sentence X in the story, GLUCOSE captures ten dimensions of causal explanation related to X. These dimensions, inspired by human cognitive psychology, cover often-implicit causes and effects of X, including events, location, possession, and other attributes.… See the full description on the dataset page: https://huggingface.co/datasets/community-datasets/glucose.flashmini-data-v1
FlashMini data v4 (card)
Deterministic FlashMini training corpus. Canonical documents live in
Parquet+ZSTD shards under shards/; each shard carries a manifest with
sha256, counts, and distributions; the frozen corpus identity is
corpus_fingerprint_sha256.
Sources and redistribution: each source carries one of mirror_allowed,
recipe_only, gated_recipe_only, review_required, generated_owned
(fail-closed; see registry/sources.yaml + source_snapshot.lock.json).
Content shards are… See the full description on the dataset page: https://huggingface.co/datasets/mjaso/flashmini-data-v1.moss-002-sft-data
Dataset Card for "moss-002-sft-data"
Dataset Summary
An open-source conversational dataset that was used to train MOSS-002. The user prompts are extended based on a small set of human-written seed prompts in a way similar to Self-Instruct. The AI responses are generated using text-davinci-003. The user prompts of en_harmlessness are from Anthropic red teaming data.
Data Splits
name
# samples
en_helpfulness.json
419049
en_honesty.json
112580… See the full description on the dataset page: https://huggingface.co/datasets/OpenMOSS-Team/moss-002-sft-data.ru-big-russian-dataset
Big Russian Dataset
Made by ZeroAgency.ru - telegram channel.
Dataset size
Train: 1 710 601 samples (filtered from 2_149_360)
Test: 18 520 samples (not filtered)
English
The Big Russian Dataset is a combination of various primarily Russian‑language datasets. With some sort of reasoning!
The dataset was deduplicated, cleaned, scored using gpt-4.1 and filtered.
Русский
Big Russian Dataset - большой русский датасет. Комбинация из… See the full description on the dataset page: https://huggingface.co/datasets/ZeroAgency/ru-big-russian-dataset.speculators-ci-datasets
speculator-tutorial
Raw vs. on-policy regenerated conversation data for training speculative-decoding
drafters (EAGLE-3 / DFlash / DSpark style), with the original source data kept alongside
so you can see exactly what regeneration changes and why it matters.
Prompts come from UltraChat-200k. The verifier / teacher model is Qwen/Qwen3-8B.
Why regenerate at all?
A speculative-decoding drafter is trained to predict what the verifier would say next.
If you train it… See the full description on the dataset page: https://huggingface.co/datasets/inference-optimization/speculators-ci-datasets.KoHRM-Text-1.4B-prepared-data
KoHRM-Text-1.4B Prepared Data
This dataset repository contains prepared HRM-Text V1Dataset artifacts for KoHRM-Text-1.4B.
The data is intended for continued pretraining and staged training with the project code at:
https://github.com/LLM-OS-Models/KoHRM-text
https://huggingface.co/LLM-OS-Models/KoHRM-Text-1.4B
https://huggingface.co/LLM-OS-Models/HRM-Text-Ko-Terminal-Tokenizer-131K
The upstream architecture and training method are based on:
Paper:… See the full description on the dataset page: https://huggingface.co/datasets/LLM-OS-Models/KoHRM-Text-1.4B-prepared-data.liquidrandom-data
liquidrandom-data
Diverse seed data for ML/LLM training data generation pipelines.
Used by the liquidrandom Python package.
Dataset Summary
This dataset contains 520,080 seed data samples across 24 categories,
generated using a hierarchical taxonomy tree approach with LLM-based quality validation
and fuzzy deduplication. Data is stored as Parquet with zstd compression.
Categories
Category
Samples
File
Coding Tasks
30,069… See the full description on the dataset page: https://huggingface.co/datasets/mlech26l/liquidrandom-data.hashed_data
Munch Hashed Index - Lightweight Audio Reference Dataset
📖 Overview
Munch Hashed Index is a lightweight reference dataset that provides SHA-256 hashes for all audio files in the Munch Urdu TTS Dataset. Instead of storing 1.27 TB of raw audio, this index stores only metadata and cryptographic hashes, enabling:
✅ Fast duplicate detection across 4.17 million audio samples
✅ Efficient dataset exploration without downloading terabytes
✅ Quick metadata queries (voice… See the full description on the dataset page: https://huggingface.co/datasets/humair025/hashed_data.companies-dataset
Tracki - Synthetic Companies Dataset
10,196 synthetic companies x 18 columns. Every one of the 15 content
fields was written by a language model; nothing is rule-generated. Built for the Tracki final
project (RUNI - Intro to Data Science): describe a company, and Tracki returns the
3 most similar companies (embeddings). This would be used for subsribing to their social media and websites.
Every row is fictional. Where the generator's name prior collided with a real trademark it… See the full description on the dataset page: https://huggingface.co/datasets/tracki/companies-dataset.trajectory_data_dream_32
d3LLM Trajectory Dataset
Project Page | Paper | GitHub | Blog
This repository contains the pseudo-trajectory distillation data used for training d3LLM (pseuDo-Distilled Diffusion Large Language Model), as introduced in the paper "d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation".
Introduction
d3LLM is a framework designed to strike a balance between accuracy and parallelism in diffusion-based large language models (dLLMs). This dataset consists of… See the full description on the dataset page: https://huggingface.co/datasets/d3LLM/trajectory_data_dream_32.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.