datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
FineFineWeb
FineFineWeb: A Comprehensive Study on Fine-Grained Domain Web Corpus
arXiv: Coming Soon
Project Page: Coming Soon
Blog: Coming Soon
Data Statistics
Domain (#tokens/#samples)
Iteration 1 Tokens
Iteration 2 Tokens
Iteration 3 Tokens
Total Tokens
Iteration 1 Count
Iteration 2 Count
Iteration 3 Count
Total Count
aerospace
5.77B
261.63M
309.33M
6.34B
9100000
688505
611034
10399539
agronomy
13.08B
947.41M
229.04M
14.26B
15752828
2711790
649404
19114022… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/FineFineWeb.FineWeb-HQ
FineWeb-HQ
Dataset Summary
FineWeb-HQ is a high-quality, model-filtered pretraining dataset derived as a subset of FineWeb. FineWeb-HQ was created by selecting the top 10% of FineWeb documents based on a deep learning classifier trained to identify structured and knowledge-rich samples. This classifier uses XLM-RoBERTa embeddings to score documents.
To validate our approach, we pretrained 1B-parameter LLM models with a Llama-like architecture across multiple… See the full description on the dataset page: https://huggingface.co/datasets/epfml/FineWeb-HQ.fineweb-edu
📚 FineWeb-Edu
1.3 trillion tokens of the finest educational data the 🌐 web has to offer
Paper: https://arxiv.org/abs/2406.17557
What is it?
📚 FineWeb-Edu dataset consists of 1.3T tokens and 5.4T tokens (FineWeb-Edu-score-2) of educational web pages filtered from 🍷 FineWeb dataset. This is the 1.3 trillion version.
To enhance FineWeb's quality, we developed an educational quality classifier using annotations generated by LLama3-70B-Instruct. We… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu.fineweb
🍷 FineWeb
15 trillion tokens of the finest data the 🌐 web has to offer
What is it?
The 🍷 FineWeb dataset consists of more than 18.5T tokens (originally 15T tokens) of cleaned and deduplicated english web data from CommonCrawl. The data processing pipeline is optimized for LLM performance and ran on the 🏭 datatrove library, our large scale data processing library.
🍷 FineWeb was originally meant to be a fully open replication of 🦅 RefinedWeb, with a… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/fineweb.HPLT2.0_cleanedNB: HPLT2.0 is now superseded by a newer release:
HPLT3.0
We recommed switching to v3.0, unless you have a compelling reason to stay on 2.0.
This is a large-scale collection of web-crawled documents in 191 world languages, produced by the HPLT project.
The source of the data is mostly Internet Archive with some additions from Common Crawl.
For a detailed description of the dataset, please refer to our website and our pre-print.
The Cleaned variant of HPLT Datasets v2.0
This is… See the full description on the dataset page: https://huggingface.co/datasets/HPLT/HPLT2.0_cleaned.stack-v3-train
🥞 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/HuggingFaceCode/stack-v3-train.finephrase
Dataset Card for HuggingFaceFW/finephrase
Dataset Summary
Synthetic data generated by DataTrove:
Model: HuggingFaceTB/SmolLM2-1.7B-Instruct (main)
Source dataset: HuggingFaceFW/fineweb-edu, config sample-350BT, split train
Generation config: temperature=1.0, top_p=1.0, top_k=50, max_tokens=2048, model_max_context=8192
Speculative decoding: {"method":"suffix","num_speculative_tokens":32}
System prompt: None
Input column: text
Prompt families:
faq prompt
Rewrite… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/finephrase.arxiv-complete
arXiv Complete Corpus
A snapshot of arXiv's metadata, version history, submission files and rendered
documents. It covers 3,148,796 papers and includes file contents, paths, sizes
and SHA-256 digests. Metadata comes from arXiv's OAI-PMH arXivRaw interface;
files come from the GCS mirror, S3 source archives and direct PDF fetches.
This release holds a PDF for 99.47% of papers and 99.54% of versions reported
with a non-zero submission size. It is a one-off snapshot; coverage gaps… See the full description on the dataset page: https://huggingface.co/datasets/secemp9/arxiv-complete.gpqa
Dataset Card for GPQA
GPQA is a multiple-choice, Q&A dataset of very hard questions written and validated by experts in biology, physics, and chemistry. When attempting questions out of their own domain (e.g., a physicist answers a chemistry question), these experts get only 34% accuracy, despite spending >30m with full access to Google.
We request that you do not reveal examples from this dataset in plain text or images online, to reduce the risk of leakage into foundation… See the full description on the dataset page: https://huggingface.co/datasets/Idavidrein/gpqa.fineweb-2
🥂 FineWeb2
A sparkling update with 1000s of languages
What is it?
This is the second iteration of the popular 🍷 FineWeb dataset, bringing high quality pretraining data to over 1000 🗣️ languages.
The 🥂 FineWeb2 dataset is fully reproducible, available under the permissive ODC-By 1.0 license and extensively validated through hundreds of ablation experiments.
In particular, on the set of 9 diverse languages we used to guide our processing decisions, 🥂… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/fineweb-2.PresentBench
PresentBench: A Fine-Grained Rubric-Based Benchmark for Slide Generation
[🌐 Homepage] [📖 Paper] [💻 Code]
This repository hosts the PresentBench benchmark dataset.
📄 Abstract
Slides serve as a critical medium for conveying information in presentation-oriented scenarios such as academia, education, and business. Despite their importance, creating high-quality slide decks remains time-consuming and cognitively demanding. Recent advances in generative models, such… See the full description on the dataset page: https://huggingface.co/datasets/PresentBench/PresentBench.fineweb-edu-fortified
Fineweb-Edu-Fortified
The composition of fineweb-edu-fortified, produced by automatically clustering a 500k row sample in
Airtrain
What is it?
Fineweb-Edu-Fortified is a dataset derived from
Fineweb-Edu by applying exact-match
deduplication across the whole dataset and producing an embedding for each row. The number of times
the text from each row appears is also included as a count column. The embeddings were produced
using TaylorAI/bge-micro
Fineweb and… See the full description on the dataset page: https://huggingface.co/datasets/airtrain-ai/fineweb-edu-fortified.infini-news-corpus
INFINI-NEWS Corpus
🔎 Search this corpus online: query it with sub-second full-text search and n-gram counts — in the browser or via a public, keyless REST API, no download required — at infini-news.uni-graz.at (API reference).
A multilingual news corpus extracted from
Common Crawl CC-News WARC files.
One row per article, with body text extracted via
trafilatura,
WARC provenance, and derived metadata (publish date, language, topic,
byte hashes) in a single flat schema. Covers… See the full description on the dataset page: https://huggingface.co/datasets/ruggsea/infini-news-corpus.FineFineWeb-sample
FineFineWeb: A Comprehensive Study on Fine-Grained Domain Web Corpus
arXiv: Coming Soon
Project Page: Coming Soon
Blog: Coming Soon
Data Statistics
Domain (#tokens/#samples)
Iteration 1 Tokens
Iteration 2 Tokens
Iteration 3 Tokens
Total Tokens
Iteration 1 Count
Iteration 2 Count
Iteration 3 Count
Total Count
aerospace
5.77B
261.63M
309.33M
6.34B
9100000
688505
611034
10399539
agronomy
13.08B
947.41M
229.04M
14.26B
15752828
2711790
649404
19114022
artistic… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/FineFineWeb-sample.finepdfs
Liberating 3T of the finest tokens from PDFs
What is this?
As we run out of web pages to process, the natural question has always been: what to do next? Only a few knew about a data source that everyone avoided for ages, due to its incredible extraction cost and complexity: PDFs.
📄 FinePDFs is exactly that. It is the largest publicly available corpus sourced exclusively from PDFs, containing about 3 trillion tokens across 475 million documents in 1733 languages.
Compared to… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/finepdfs.Magicoder-OSS-Instruct-75KThis is the OSS-Instruct dataset generated by gpt-3.5-turbo-1106 developed by OpenAI. Please pay attention to OpenAI's usage policy when adopting this dataset: https://openai.com/policies/usage-policies.
UltraData-Code
UltraData-Code
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series |
📖 Tech Report (Coming Soon) |
🤗 UltraData-Code-L2 Classifier
English | 中文
📚 Introduction
UltraData-Code is a complete implementation of the UltraData L0-L4 tiered data management framework. It covers four code data states from L0 through L3, with each level corresponding to a distinct construction stage. The pipeline starts from approximately 192 million public GitHub… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-Code.fineweb-tokenized
FineWeb Tokenized
> 4 trillion tokens of the pre-tokenized data the 🌐 web has to offer
What is it?
This is a pre-tokenized version of the HuggingFaceFW/fineweb dataset (currently in-progress, tokenization of the ~15 trillion tokens corpus is ongoing). The data is being pre-processed and tokenized using the AnisoleAI BPE tokenizer (52,022 vocabulary size) and packed into compact uint16 Parquet shards.
By distributing the pre-tokenized corpus, we eliminate… See the full description on the dataset page: https://huggingface.co/datasets/anisoleai/fineweb-tokenized.TxT360-v2
TxT360-v2
Dataset Description
Pre-training sources for the K2 Horizon training data release. This repository is part of the K2 Horizon collection.
The repository is organized into multiple subsets. Every subset has a train split backed by Parquet shards.
K2 Horizon Dataset Series
Dataset repository
Focus
Subsets
IFM/TxT360-v2
Web and question-answering text
3
IFM/Code-Reasoning
Code reasoning and task synthesis
7
IFM/Math-Reasoning… See the full description on the dataset page: https://huggingface.co/datasets/IFM/TxT360-v2.finetranslations
💬 FineTranslations
The world's knowledge in 1+1T tokens of parallel text
What is it?
This dataset contains over 1 trillion tokens of parallel text in English and 500+ languages. It was obtained by translating data from 🥂 FineWeb2 into English using Gemma3 27B.
We relied on datatrove's inference runner to deploy a synthetic data pipeline at scale. Its checkpointing and VLLM lifecycle management features allowed us to use leftover compute from the HF cluster… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/finetranslations.AutoMathText-V2
🚀 AutoMathText-V2: A 2.46 Trillion Token AI-Curated STEM Pretraining Dataset
🎉 AutoMathText-v2 has surpassed 1.5 million downloads! We'd love to know how you're using it. Please take 1 minute to fill out our use case survey. Your feedback will directly shape the future roadmap of this dataset.👉 Share your use case here
📊 AutoMathText-V2 consists of 2.46 trillion tokens of high-quality, deduplicated text spanning web content, mathematics, code, reasoning, and… See the full description on the dataset page: https://huggingface.co/datasets/OpenSQZ/AutoMathText-V2.FineWeb2-HQ
FineWeb2-HQ
Dataset summary
FineWeb2-HQ is a high-quality, model-filtered pretraining dataset derived as a subset of FineWeb2, spanning 20 languages. It enables around 6x faster pretraining compared to the base dataset. FineWeb2-HQ was created by selecting the top 10% quality documents of FineWeb2 in each language, based on scores assigned by a deep learning classifier trained to identify structured and knowledge-rich samples using XLM-RoBERTa embeddings.
Validation… See the full description on the dataset page: https://huggingface.co/datasets/epfml/FineWeb2-HQ.ultrafeedback-binarized-preferences-cleaned
UltraFeedback - Binarized using the Average of Preference Ratings (Cleaned)
This dataset represents a new iteration on top of argilla/ultrafeedback-binarized-preferences,
and is the recommended and preferred dataset by Argilla to use from now on when fine-tuning on UltraFeedback.
Read more about Argilla's approach towards UltraFeedback binarization at argilla/ultrafeedback-binarized-preferences/README.md.
Differences with argilla/ultrafeedback-binarized-preferences… See the full description on the dataset page: https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned.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.the-stack-smol
Dataset Description
A small subset (~0.1%) of the-stack dataset, each programming language has 10,000 random samples from the original dataset. The dataset has 2.6GB of text (code).
Languages
The dataset contains 30 programming languages:
"assembly", "batchfile", "c++", "c", "c-sharp", "cmake", "css", "dockerfile", "fortran", "go", "haskell", "html", "java",
"javascript", "julia", "lua", "makefile", "markdown", "perl", "php", "powershell", "python", "ruby", "rust"… See the full description on the dataset page: https://huggingface.co/datasets/bigcode/the-stack-smol.distilabel-capybara-dpo-7k-binarized
Capybara-DPO 7K binarized
A DPO dataset built with distilabel atop the awesome LDJnr/Capybara
This is a preview version to collect feedback from the community. v2 will include the full base dataset and responses from more powerful models.
Why?
Multi-turn dialogue data is key to fine-tune capable chat models. Multi-turn preference data has been used by the most relevant RLHF works (Anthropic, Meta Llama2, etc.). Unfortunately, there are very few… See the full description on the dataset page: https://huggingface.co/datasets/argilla/distilabel-capybara-dpo-7k-binarized.flores_101One of the biggest challenges hindering progress in low-resource and multilingual machine translation is the
lack of good evaluation benchmarks. Current evaluation benchmarks either lack good coverage of low-resource
languages, consider only restricted domains, or are low quality because they are constructed using
semi-automatic procedures. In this work, we introduce the FLORES evaluation benchmark, consisting of 3001
sentences extracted from English Wikipedia and covering a variety of different topics and domains.
These sentences have been translated in 101 languages by professional translators through a carefully
controlled process. The resulting dataset enables better assessment of model quality on the long tail of
low-resource languages, including the evaluation of many-to-many multilingual translation systems, as all
translations are multilingually aligned. By publicly releasing such a high-quality and high-coverage dataset,
we hope to foster progress in the machine translation community and beyond.vllm-control-arena
vLLM Main Tasks Dataset
AI coding tasks generated from vLLM git commits
Dataset Description
This dataset contains 6801 coding tasks automatically generated from git commits in the vLLM repository. Each task represents a real-world coding challenge derived from actual development work.
Dataset Structure
The dataset contains the following columns:
commit_hash: The git commit hash
parent_hash: The parent commit hash
commit_title: The original commit… See the full description on the dataset page: https://huggingface.co/datasets/RoganInglis/vllm-control-arena.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.explicit-edit-benchmark
Explicit Edit Benchmark
226 deterministic exact-edit tasks, run by different agents, harnesses, models and configurations. Every observation records what the harness did and whether the resulting files matched byte for byte.
Source code and benchmark runner: GitHub — Explicit Edit Benchmark
Open the interactive Explorer to compare agents, harnesses, models, versions, reasoning modes, correctness, recovery, time, cost and tokens.
Leaderboard by model route
Score v2… See the full description on the dataset page: https://huggingface.co/datasets/alexshpunt/explicit-edit-benchmark.