datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.fineweb-edu-translated
Helsinki-NLP/fineweb-edu-translated
fineweb-edu-tanslated is a collection of automatically translated documents from fineweb-edu.
Translations are based on OPUS-MT and HPLT-MT models.
The data in v1.0 covers 36,704,000 documents with over 28 billion space-searated tokens of English data translated into 36 languages.
The total v1.0 data set includes over 960 billion tokens and the translated documents are aligned across all languages.
In the v1.1 release, additional translations… See the full description on the dataset page: https://huggingface.co/datasets/Helsinki-NLP/fineweb-edu-translated.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.Ultra-FineWeb
Ultra-FineWeb
📜 Technical Report |
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM4 Series |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
Ultra-FineWeb is a large-scale, high-quality, and efficiently-filtered dataset. We use the proposed efficient verification-based high-quality filtering pipeline to the FineWeb and Chinese FineWeb datasets (source data from Chinese FineWeb-edu-v2, which includes IndustryCorpus2, MiChao, WuDao, SkyPile… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/Ultra-FineWeb.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.FineWeb-10B
Qdrant-FineWeb-10B
Overview
Qdrant-FineWeb-10B (Q-FineWeb-10B) is a 10-billion-vector retrieval benchmark derived from FineWeb. Each document is represented with dense and sparse embeddings from Alibaba-NLP/gte-multilingual-base, alongside its original FineWeb payload and metadata. The benchmark also includes exact brute-force ground truth for ~120,000 MS MARCO queries.
The dataset includes:
10 billion dense embeddings
10 billion sparse embeddings
FineWeb… See the full description on the dataset page: https://huggingface.co/datasets/Qdrant/FineWeb-10B.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.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.Ultra-FineWeb-L1
Ultra-FineWeb-L1
📜 Ultra-FineWeb Technical Report |
📦 UltraData Collection |
🌐 UltraData
English |
中文
📚 Introduction
Ultra-FineWeb-L1 is a large-scale English web corpus built from Common Crawl snapshots. Within UltraData's L0-L4 tiered data management framework, it serves as the L1 filtered layer for general web data and provides the foundation for subsequent L2 selection and L3 refinement. Building on the FineWeb processing pipeline, we perform… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/Ultra-FineWeb-L1.Ultra-FineWeb-L3
Ultra-FineWeb-L3
📜 Ultra-FineWeb Technical Report |
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
Ultra-FineWeb-L3 is the L3 refined data for general high-quality web data within UltraData's L0-L4 tiered data management framework. Moving beyond L2 quality selection, it transforms high-value web corpora into structured, high-learnability training data with clearer reasoning signals and richer educational… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/Ultra-FineWeb-L3.FineWeb2-embedded
FineWeb2-embedded
Dataset summary
FineWeb2-embedded is an extension of the FineWeb2 dataset, annotated with document-level XLM-RoBERTa embeddings for 20 languages, making the dataset useful for a variety of tasks, including document clustering, filtering, and other multilingual research.
Since XLM-RoBERTa has a sequence length limit of 512 tokens, each document's embeddings are obtained by mean-pooling 512 token chunks of the XLM-RoBERTa output. Therefore, longer texts… See the full description on the dataset page: https://huggingface.co/datasets/epfml/FineWeb2-embedded.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.chinese-fineweb-edu
This version is deprecated. We recommend you to use the newest version Fineweb-edu-chinese-v2.1 !
Chinese Fineweb Edu Dataset [中文] [English]
[OpenCSG Community] [👾github] [wechat] [Twitter]
📖Technical Report
Chinese Fineweb Edu dataset is a meticulously constructed high-quality Chinese pre-training corpus, specifically designed for natural language processing tasks in the education domain. This dataset undergoes a rigorous selection and… See the full description on the dataset page: https://huggingface.co/datasets/opencsg/chinese-fineweb-edu.fineweb-edu-100b-shufflefineweb
🍷 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/idleengine/fineweb.fineweb-edu
Pre-shuffled fineweb-edu dataset
irish_fineweb_eduData translation project of https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu, sample-10BT subset. Data are translated from English to Irish using NLLB-3.3B.
fineweb-2-sentence-splitFineweb 2 split into sentences. Instances per languages were sampled by us to balance the data w.r.t. Fineweb-edu.
To split the text into sentences we used the sat3-l model from the wtpsplit library.
We fix a sentence threshold of 0.02 and a maximum sentence length of 256.
If you use this dataset, you should cite:
@misc{penedo2025fineweb2pipelinescale,
title={FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language},
author={Guilherme Penedo and… See the full description on the dataset page: https://huggingface.co/datasets/mimir-lcm/fineweb-2-sentence-split.opc-fineweb-code-corpus
OpenCoder Dataset
The OpenCoder dataset is composed of the following datasets:
opc-sft-stage1: the sft data used for opencoder sft-stage1
opc-sft-stage2: the sft data used for opencoder sft-stage2
opc-annealing-corpus: the synthetic data & algorithmic corpus used for opencoder annealing
opc-fineweb-code-corpus: the code-related page recalled from fineweb <-- you are here
opc-fineweb-math-corpus: the math-related page recalled from finewebrefineCode-code-corpus-meta: the meta-data… See the full description on the dataset page: https://huggingface.co/datasets/OpenCoder-LLM/opc-fineweb-code-corpus.fineweb-edu-gpt2fineweb_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.fineweb-edu-hindi
Fineweb-edu-hindi
Fineweb-edu-hindi is a synthetic dataset generated by translating the Fineweb-edu to Hindi Language using IndicTrans2.
The model variant used is IndicTrans2-en-indic-dist-200M. It contains about 300 Billion tokens in the Gemma-2-2b Tokenizer.
Hardware Resources:
The Google Cloud TPUs and the Google Cloud Platform was utilized for the dataset creation process.
Code:
Github: fineweb-translation
Contact:
If any queries or issues… See the full description on the dataset page: https://huggingface.co/datasets/KathirKs/fineweb-edu-hindi.fineweb-c
FineWeb-C: Educational content in many languages, labelled by the community
Multilingual data is better together!
Note: We are not actively working on this project anymore. You can continue to contribute annotations and we'll occasionally refresh the exported data.
What is this?
FineWeb-C is a collaborative, community-driven project that expands upon the FineWeb2 dataset. The goal is to create high-quality educational content annotations across… See the full description on the dataset page: https://huggingface.co/datasets/data-is-better-together/fineweb-c.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/chilomax/fineweb-edu.fineweb-2-turkish-categorized
What is this
THis is the categorized version of the Turkish subset of the fineweb-2 dataset.
It is an ongoing effort, and the details will be added soon with the rest of the dataset.
chinese-fineweb-edu-v2
This version is deprecated. We recommend you to use the newest version Fineweb-edu-chinese-v2.1 !
Chinese Fineweb Edu Dataset V2 [中文] [English]
[OpenCSG Community] [👾github] [wechat] [Twitter]
📖Technical Report
Chinese Fineweb Edu Dataset V2 is a comprehensive upgrade of the original Chinese Fineweb Edu, designed and optimized for natural language processing (NLP) tasks in the education sector. This high-quality Chinese pretraining dataset has… See the full description on the dataset page: https://huggingface.co/datasets/opencsg/chinese-fineweb-edu-v2.fineweb-nopotter
📚 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 then… See the full description on the dataset page: https://huggingface.co/datasets/MindlessForMinerva/fineweb-nopotter.fineweb-2-edu-korean-rawHuggingFaceFW/fineweb-2 (v2.1.0)
It took about 9 hours on A100 80gbx4 to process the dataset.