datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.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.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.smollm-corpus
SmolLM-Corpus
This dataset is a curated collection of high-quality educational and synthetic data designed for training small language models.
You can find more details about the models trained on this dataset in our SmolLM blog post.
Dataset subsets
Cosmopedia v2
Cosmopedia v2 is an enhanced version of Cosmopedia, the largest synthetic dataset for pre-training, consisting of over 39 million textbooks, blog posts, and stories generated by… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus.smoltalk
SmolTalk
Dataset description
This is a synthetic dataset designed for supervised finetuning (SFT) of LLMs. It was used to build SmolLM2-Instruct family of models and contains 1M samples. More details in our paper https://arxiv.org/abs/2502.02737
During the development of SmolLM2, we observed that models finetuned on public SFT datasets underperformed compared to other models with proprietary instruction datasets. To address this gap, we created new synthetic datasets… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceTB/smoltalk.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.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.finemath
📐 FineMath
What is it?
📐 FineMath consists of 34B tokens (FineMath-3+) and 54B tokens (FineMath-3+ with InfiMM-WebMath-3+) of mathematical educational content filtered from CommonCrawl. To curate this dataset, we trained a mathematical content classifier using annotations generated by LLama-3.1-70B-Instruct. We used the classifier to retain only the most educational mathematics content, focusing on clear explanations and step-by-step problem solving rather than… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceTB/finemath.drlc-leaderboard-dataCADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/huggingface/CADS-dataset.ultrafeedback_binarized
Dataset Card for UltraFeedback Binarized
Dataset Description
This is a pre-processed version of the UltraFeedback dataset and was used to train Zephyr-7Β-β, a state of the art chat model at the 7B parameter scale.
The original UltraFeedback dataset consists of 64k prompts, where each prompt is accompanied with four model completions from a wide variety of open and proprietary models. GPT-4 is then used to assign a score to each completion, along criteria like… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized.fineweb-edu-score-2
📚 FineWeb-Edu-score-2
1.3 trillion tokens of the finest educational data the 🌐 web has to offer
What is it?
📚 FineWeb-Edu dataset consists of 1.3T tokens (FineWeb-Edu) and 5.4T tokens of educational web pages filtered from 🍷 FineWeb dataset. This is the 5.4 trillion version.
Note: this version uses a lower educational score threshold = 2, which results in more documents, but lower quality compared to the 1.3T version. For more details check the… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu-score-2.finepdfs_lang_classificationfinepdfs-edu
📚 FinePDFs-Edu
350B+ of highly educational tokens from PDFs 📄
What is it?
📚 FinePDFs-Edu dataset consists of 350B+ tokens of educational PDFs filtered from 📄 FinePDFs dataset covering 69 languages.
FinePDFs was created using the formula inspired from FineWeb-Edu, we developed an educational quality classifier using annotations generated by Qwen3-235B-A22B-Instruct-2507 for each of 69 languages present in this dataset.
We then used this classifier to retain only the… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/finepdfs-edu.finewiki
This is an updated and better extracted version of the wikimedia/Wikipedia dataset originally released in 2023. We carefully parsed Wikipedia HTML dumps from August of 2025 covering 325 languages.
This dataset:
fully renders templates as it was extracted from HTML and not markdown dumps
removes redirects, disambiguation, and other non main article pages
includes detailed metadata such as page ID, title, last modified date, wikidate ID, version and markdown version of the textpreserves… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/finewiki.stack-edu
💻 Stack-Edu
Stack-Edu is a 125B token dataset of educational code filtered from The Stack v2, precisely the curated training corpus of StarCoder2 models denoted StarCoder2Data. It is intended for Language Models training.
This dataset was curated using a classifier-based filtering strategy, inspired by 📚 FineWeb-Edu, to retain only the highest-quality educational programming content.
Stack-Edu shows consistent improvement over StarCoder2data on all the programming languages on… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceTB/stack-edu.fineweb_edu_100BT-shuffled
FineWeb-Edu 100BT (Shuffled)
A globally shuffled version of HuggingFaceFW/fineweb_edu_100BT.
Part of the Smol-Data collection — tried and tested mixes for strong pretraining.
Dataset Description
This dataset contains the same ~100B tokens as fineweb_edu_100BT but with all documents globally shuffled (seed=42). Use this version when you need randomized document ordering for pretraining.
How It Was Created
The unshuffled dataset was loaded into memory, shuffled… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/fineweb_edu_100BT-shuffled.REDDIT_threaded
Dataset Card for "REDDIT_threaded"
More Information needed
CXM_Arena
Dataset Card for CXM Arena Benchmark Suite
Dataset Description
This dataset, "CXM Arena Benchmark Suite," is a comprehensive collection designed to evaluate various AI capabilities within the Customer Experience Management (CXM) domain. It consolidates five distinct tasks into a unified benchmark, enabling robust testing of models and pipelines in business contexts. The entire suite was synthetically generated using advanced large language models, primarily… See the full description on the dataset page: https://huggingface.co/datasets/sprinklr-huggingface/CXM_Arena.Deep-RL-Course-Certificationfinetranslations-edu
💬 FineTranslations
The world's knowledge in 1+1T tokens of parallel text
NOTE: this is the Edu version of the dataset, containing only the top 10% scoring data based on an educational classifier applied to the English translations. It has no splits. For the base dataset, see here.
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… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/finetranslations-edu.carbon-pretraining-corpus
🧬 Carbon Pretraining Corpus
Description
173M DNA & RNA sequences · 1.1 trillion nucleotides — the DNA pretraining mixture used to train Carbon, a genomic foundation model.
This dataset is a collection of data sources intended for training genomic foundation models, such as Carbon. It contains DNA and RNA sequences spanning eukaryote and prokaryote species.
Across the four main configs it totals 1.1 T DNA base pairs (180B tokens with Carbon's 6-mer tokenizer). A… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceBio/carbon-pretraining-corpus.dclm-edu
DCLM-Edu
Description
This is a filtered version of DCLM dataset using FineWeb-Edu educational quality classifier. We annotate each web page based on the educational quality
on a scale from 0 to 5 and only keep samples with a score higher than 2. This dataset is intended for small language models training and was used to train SmolLM2-135M and SmolLM2-360M.
Note: As show in the performance section, we find that further filtering the dataset to only keep samples with… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceTB/dclm-edu.dclm_100BT
DCLM 100BT
A ~100 billion token English subset of DCLM-Baseline 1.0, created for efficient pretraining experiments.
Part of the Smol-Data collection — tried and tested mixes for strong pretraining.
Dataset Description
This dataset was created by randomly sampling from the full DCLM-Baseline 1.0 dataset (~3.5T tokens) to produce a ~100B token subset. Sampling was performed with a fixed seed (42) and a slight 1.05× oversampling factor to account for variance.
A pre-shuffled… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/dclm_100BT.dclm_100BT-shuffled
DCLM 100BT (Shuffled)
A globally shuffled version of HuggingFaceFW/dclm_100BT.
Part of the Smol-Data collection — tried and tested mixes for strong pretraining.
Dataset Description
This dataset contains the same ~100B tokens as dclm_100BT but with all documents globally shuffled (seed=42). Use this version when you need randomized document ordering for pretraining.
How It Was Created
The unshuffled dataset was loaded into memory, shuffled with… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/dclm_100BT-shuffled.agent-usage
Agent Usage on the Hugging Face Hub
Coding agents are real users of the Hugging Face Hub. Claude Code, Codex, Cursor, and a growing list of harnesses are searching for models, building and pushing datasets, training models on Jobs, spinning up Spaces — tens of millions of requests so far (hf CLI for agents). Now there's public data on which ones.
Requests made through the huggingface_hub library (including the hf CLI) carry an agent/<name> User-Agent token identifying the… See the full description on the dataset page: https://huggingface.co/datasets/huggingface/agent-usage.fineweb_100BT-shuffled
FineWeb 100BT (Shuffled)
A globally shuffled version of HuggingFaceFW/fineweb_100BT.
Part of the Smol-Data collection — tried and tested mixes for strong pretraining.
Dataset Description
This dataset contains the same ~100B tokens as fineweb_100BT but with all documents globally shuffled (seed=42). Use this version when you need randomized document ordering for pretraining.
How It Was Created
The unshuffled dataset was loaded into memory, shuffled with… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceFW/fineweb_100BT-shuffled.CXM_Arena_French
Dataset Card for CXM Arena French Benchmark Suite
Dataset Description
This dataset, "CXM Arena French Benchmark Suite," is a comprehensive collection designed to evaluate various AI capabilities within the Customer Experience Management (CXM) domain, specifically for the French language. It is closely modeled after the original CXM_Arena benchmark, but all data is in French. The suite consolidates five distinct tasks into a unified benchmark, enabling robust testing of… See the full description on the dataset page: https://huggingface.co/datasets/sprinklr-huggingface/CXM_Arena_French.