datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
soc-ratchakitcha
Royal Gazette Thailand (Ratchakitcha) Dataset
ชุดข้อมูลราชกิจจานุเบกษา (แบบ Machine Readable)
โครงการ Open Law Data Thailand ร่วมกับคณะกรรมาธิการการพาณิชย์และการอุตสาหกรรม วุฒิสภา ได้รับความอนุเคราะห์ข้อมูลจาก สำนักเลขาธิการคณะรัฐมนตรี (สลค.) เพื่อเผยแพร่ข้อมูลกฎหมายไทยสู่สาธารณะในรูปแบบที่ประมวลผลได้ด้วยคอมพิวเตอร์ (Machine Readable) เพื่อส่งเสริมนวัตกรรม Legal Tech และ AI ของประเทศไทย
Dataset Description
ชุดข้อมูลนี้รวบรวมรายการประกาศในราชกิจจานุเบกษา… See the full description on the dataset page: https://huggingface.co/datasets/open-law-data-thailand/soc-ratchakitcha.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.Company-document-dataset-v2
Company Documents v2
Generation complete: all 13 document types have completed export and upload checkpoints.
Synthetic, born-digital business documents rendered from four open sample databases, with exact gold
labels: 353,580 PDFs (404,514 pages) of 13 document types in
English and French, issued by 60 synthetic companies,
each with its own letterhead, numbering and wording. Successor of
CompanyDocuments (2,677 PDFs, 4 types).
Dataset overview
property… See the full description on the dataset page: https://huggingface.co/datasets/AyoubChLin/Company-document-dataset-v2.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)
4,427,314
Comments (platform total)
13,538,160
Posts (collected)
422,497
Comments (collected)
3,723,066
Agents
57,217
Social graph edges
826… See the full description on the dataset page: https://huggingface.co/datasets/takschdube/moltbook-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.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.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.ICPC_Data
ICPC World Finals — a discriminative subset, with model traces
24 ICPC World Finals problems (2021–2025), together with 1440 full contest transcripts
of an LLM attempting them under simulated contest rules across three arms: with no hint,
with the official editorial as a hint, and with a hint written by a second model that gets
10 rounds of measured feedback to improve it.
Selection
The agent
Every contest run in this dataset comes from:… See the full description on the dataset page: https://huggingface.co/datasets/xupy21/ICPC_Data.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.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.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.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.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.jabarti-llm-dataset
jabarti-llm-dataset
Cleaned, section-chunked training corpus for a small bilingual LLM
(Arabic + English), combining a curated Egyptian-history collection with
general Wikipedia coverage from
CohereLabs/wikipedia-2023-11-embed-multilingual-v3.
Every pretrain record is a contiguous span of 120-1500 characters with the
article title and section headings removed. Provenance is in ds_source.
Configs and Splits
Config
Split
Rows
Training phase
Purpose… See the full description on the dataset page: https://huggingface.co/datasets/bakrianoo/jabarti-llm-dataset.MyMentorLLM-dataset
Dataset Card for MyMentorLLM
This dataset accompanies the MyMentorLLM paper, arXiv:2607.25667, which describes the simulation environment, generation procedure, experimental design and validation analyses. If you use this dataset, please cite the paper (see Citation Information).
Dataset Summary
MyMentorLLM is a multimodal voice- and text-based deliberate-practice environment used to generate 2,100 simulated Cognitive Behavioural Therapy (CBT) training sessions… See the full description on the dataset page: https://huggingface.co/datasets/RodolfoRizzi/MyMentorLLM-dataset.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.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.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.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.FineWeb-2021
FineWeb-Edu 2021 — Cleaned and Shuffled
This dataset is a year-specific, cleaned, shuffled, and sharded release derived from HuggingFaceFW/fineweb-edu. It contains English educational web text collected in Common Crawl snapshots whose dump identifier belongs to 2021.
This is not a news-only dataset. The year refers to the Common Crawl capture year, not necessarily the page's publication year.
Dataset summary
Item
Value
Year
2021
Rows
139,636,993… See the full description on the dataset page: https://huggingface.co/datasets/DataHound26/FineWeb-2021.FineWeb-2020
FineWeb-Edu 2020 — Cleaned and Shuffled
This dataset is a year-specific, cleaned, shuffled, and sharded release derived from HuggingFaceFW/fineweb-edu. It contains English educational web text collected in Common Crawl snapshots whose dump identifier belongs to 2020.
This is not a news-only dataset. The year refers to the Common Crawl capture year, not necessarily the page's publication year.
Dataset summary
Item
Value
Year
2020
Rows
123,382,457… See the full description on the dataset page: https://huggingface.co/datasets/DataHound26/FineWeb-2020.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.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.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.SQaLe-text-to-SQL-dataset
🧮 SQALE: A Large-Scale Semi-Synthetic Dataset
SQALE is a large-scale, semi-synthetic Text-to-SQL dataset grounded in real-world database schemas.
It was designed to push the boundaries of natural language to SQL generation, combining realistic schema diversity, complex query structures, and linguistically varied natural language questions.
The dataset was introduced in the paper SQaLe: A Large Text-to-SQL Corpus Grounded in Real Schemas. The code for the generation pipeline of this… See the full description on the dataset page: https://huggingface.co/datasets/trl-lab/SQaLe-text-to-SQL-dataset.FineWeb-2022
FineWeb-Edu 2022 — Cleaned and Shuffled
This dataset is a year-specific, cleaned, shuffled, and sharded release derived from HuggingFaceFW/fineweb-edu. It contains English educational web text collected in Common Crawl snapshots whose dump identifier belongs to 2022.
This is not a news-only dataset. The year refers to the Common Crawl capture year, not necessarily the page's publication year.
Dataset summary
Item
Value
Year
2022
Rows
106,753,442… See the full description on the dataset page: https://huggingface.co/datasets/DataHound26/FineWeb-2022.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.cell2sentence4longevity-data
Dataset Card: longevity-genie/cell2sentence4longevity-data
Summary
This repository contains preprocessed single-cell RNA-seq (scRNA‑seq) datasets prepared as “cell sentences” for training and evaluation of cells2sentence-style models. Each cell is represented as a space‑separated sequence of top expressed gene symbols, enabling language‑model style training for tasks such as biological age prediction and other downstream applications.
This dataset targets fine‑tuning and… See the full description on the dataset page: https://huggingface.co/datasets/longevity-genie/cell2sentence4longevity-data.EDGAR_FILINGS_DATASET
SFD: SEC Filings Dataset (v1)
SFD-v1 is an open, layout-faithful reconstruction of U.S. Securities and Exchange Commission (SEC) EDGAR filings into token-efficient MultiMarkdown (MMD), targeted at long-context language modeling, financial reasoning, document understanding, and evaluation.
This release covers filings from January 2022 through June 2025 (~3.4M filings), produced by the SFD parser described in:
The SEC Filings Dataset: Reconstructing U.S. Corporate and Financial… See the full description on the dataset page: https://huggingface.co/datasets/anonymous-md/EDGAR_FILINGS_DATASET.R2Flow-Dataset
R² Flow Dataset
Training and test splits of R² Flow: Recursive Self-Improvement via Recursive Skill Evolution
(code: beita6969/r2flow).
Six in-distribution (IID) benchmarks supply the training tasks and the IID test sets. Six
out-of-distribution (OOD) benchmarks are evaluation-only; each is posed as one IID task type.
Benchmark
Role
Training
Test
Test source
Posed as
HotpotQA
IID
512
128
distractor validation
–
TriviaQA
IID
512
128
rc.nocontext validation
–
AIME… See the full description on the dataset page: https://huggingface.co/datasets/beita6969/R2Flow-Dataset.