Datasets
Training datasets with quantum-safe provenance
Subset of LAION-5B filtered for aesthetic quality. 600M image-text pairs scored >5.0 by aesthetic predictor. Standard for image generation training.
Multilingual speech dataset with 30K+ hours across 120+ languages. Crowdsourced and validated. De facto standard for ASR training.
Open corpus of 3T tokens for language model pretraining. Sourced from web, academic papers, code, encyclopedic, and book content.
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.
Instruction-following dataset of 52K examples generated from text-davinci-003. Foundational instruction tuning dataset.
Largest open code dataset. 67.5TB of permissively licensed source code across 600+ programming languages from Software Heritage.
Dataset Card for "wikitext" Dataset Summary The WikiText language modeling dataset is a collection of over 100 million tokens extracted from the set of verified Good and Featured articles on Wikipedia. The dataset is available under the Creative Commons Attribution-ShareAlike License. Compared to the preprocessed version of Penn Treebank (PTB), WikiText-2 is over 2 times larger and WikiText-103 is over 110 times larger. The WikiText dataset also features a far larger… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/wikitext.
Human-generated, human-annotated conversation trees. 91K messages across 35+ languages. RLHF training data.
TxT360: A Top-Quality LLM Pre-training Dataset Requires the Perfect Blend Changelog Version Details v1.1 Added new data sources: TxT360_BestOfWeb, TxT360_QA, europarl-aligned, and wikipedia_extended. Details of v1.1 Additions TxT360_BestOfWeb: This is a filtered version of the TxT360 dataset, created using the ProX document filtering model. The model is similar to the FineWeb-Edu classifier, but also assigns an additional format score that… See the full description on the dataset page: https://huggingface.co/datasets/LLM360/TxT360.
ERA5 Based on Hersbach et al. 2020 with data exposed through Copernicus C3S API 26 variable subset of data as described in Table 3 of Bonev et al. 2023. Each file contains all 26 variables sampled every 6 hours (starting with 00:00:00) for an entire month in a given year.
✨ Note: For all FineInstructions resources please visit: https://huggingface.co/fineinstructions This dataset is ~1B+ synthetic instruction-answer pairs or ~300B tokens created using the FineInstructions pipeline. The FineInstructions pipeline was run over the raw pre-training documents in the Nemotron-CC pre-training corpus (a subset of high-quality documents from CommonCrawl). See our paper for more details. Each .parquet file in the data folderhas a corresponding judge-*.json file that… See the full description on the dataset page: https://huggingface.co/datasets/fineinstructions/fineinstructions_nemotron.
Dataset Card for GSM8K Dataset Summary GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems. The dataset was created to support the task of question answering on basic mathematical problems that require multi-step reasoning. These problems take between 2 and 8 steps to solve. Solutions primarily involve performing a sequence of elementary calculations using basic arithmetic operations (+ − ×÷) to reach the… See the full description on the dataset page: https://huggingface.co/datasets/openai/gsm8k.
C4 Dataset Summary A colossal, cleaned version of Common Crawl's web crawl corpus. Based on Common Crawl dataset: "https://commoncrawl.org". This is the processed version of Google's C4 dataset We prepared five variants of the data: en, en.noclean, en.noblocklist, realnewslike, and multilingual (mC4). For reference, these are the sizes of the variants: en: 305GB en.noclean: 2.3TB en.noblocklist: 380GB realnewslike: 15GB multilingual (mC4): 9.7TB (108 subsets, one per… See the full description on the dataset page: https://huggingface.co/datasets/allenai/c4.
Dataset Card for GLUE Dataset Summary GLUE, the General Language Understanding Evaluation benchmark (https://gluebenchmark.com/) is a collection of resources for training, evaluating, and analyzing natural language understanding systems. Supported Tasks and Leaderboards The leaderboard for the GLUE benchmark can be found at this address. It comprises the following tasks: ax A manually-curated evaluation dataset for fine-grained analysis of system… See the full description on the dataset page: https://huggingface.co/datasets/nyu-mll/glue.
🍃 MINT-1T:Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens 🍃 MINT-1T is an open-source Multimodal INTerleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in… See the full description on the dataset page: https://huggingface.co/datasets/mlfoundations/MINT-1T-HTML.
Dataset Card for "ai2_arc" Dataset Summary A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also including a corpus of over 14 million science sentences relevant to… See the full description on the dataset page: https://huggingface.co/datasets/allenai/ai2_arc.
Dataset Card for MMLU Dataset Summary Measuring Massive Multitask Language Understanding by Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt (ICLR 2021). This is a massive multitask test consisting of multiple-choice questions from various branches of knowledge. The test spans subjects in the humanities, social sciences, hard sciences, and other areas that are important for some people to learn. This covers 57 tasks… See the full description on the dataset page: https://huggingface.co/datasets/cais/mmlu.
🚀 LLaVA-One-Vision-1.5-Mid-Training-85M Dataset is being uploaded 🚀 Upload Status All Completed: ImageNet-21k、LAIONCN、DataComp-1B、Zero250M、COYO700M、SA-1B、MINT、Obelics 📜 Cite If you find LLaVA-One-Vision-1.5-Mid-Training-85M useful in your research, please consider to cite the following related papers: @misc{an2025llavaonevision15fullyopenframework, title={LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training}… See the full description on the dataset page: https://huggingface.co/datasets/mvp-lab/LLaVA-OneVision-1.5-Mid-Training-85M.
FineNews FineNews is a multilingual news-text dataset for language-model research. It filters and deduplicates a 2021–2025 snapshot of the INFINI-NEWS Corpus, which extracts articles from Common Crawl CC-News. At a glance Measure FineNews Input articles 852,824,802 Infini-News rows from 2021–2025 Output 392,627,654 physical rows Files 294,509 Parquet files Folders 60 publication months (2021-01 to 2025-12), then language Language folders 129… See the full description on the dataset page: https://huggingface.co/datasets/ksolovev/fine-news.
I also seperately provide just the prompts in prompts.json keys are the image_id, and the values are the captions generated Captions generated by moondream: vikhyatk/moondream2 Latents generated by SDXL VAE: madebyollin/sdxl-vae-fp16-fix Embeddings generated by SigLIP: hf-hub:timm/ViT-SO400M-14-SigLIP-384 Original dataset: common-canvas/commoncatalog-cc-by Latents f32 and embeddings are f16 bytes Compute cost: 16x3090 for 3 day. Approximately.