Model Hub

GPIC: A Giant Permissive Image Corpus for Visual Generation Keshigeyan Chandrasegaran*1,  Kyle Sargent*1,  Suchir Agarwal1,  Michael Jang1,  Michael Poli1,2,  Juan Carlos Niebles1,4,  Justin Johnson3,  Jiajun Wu1,  Li Fei-Fei1 1 Stanford University   2 Radical Numerics   3 University of Michigan   4 Salesforce… See the full description on the dataset page: https://huggingface.co/datasets/stanford-vision-lab/gpic.

MADLAD-400 Dataset and Introduction MADLAD-400 (Multilingual Audited Dataset: Low-resource And Document-level) is a document-level multilingual dataset based on Common Crawl, covering 419 languages in total. This uses all snapshots of CommonCrawl available as of August 1, 2022. The primary advantage of this dataset over similar datasets is that it is more multilingual (419 languages), it is audited and more highly filtered, and it is document-level. The main disadvantage… See the full description on the dataset page: https://huggingface.co/datasets/allenai/MADLAD-400.

YODAS v3 Paper YODAS v3 is a large web-crawled dataset containing over 1.1 million hours of audio that were originally released under a CC-BY-3.0 license. The dataset contains audio in over 100 languages. YODAS v3 can be used for a variety of multi-modal tasks, including Automatic Speech Recognition, Text-to-Speech, and Audio Representation Learning. We crawl a distinct set of videos from the v1 and v2 versions of YODAS, to guarantee that there are no overlaps in the data. For… See the full description on the dataset page: https://huggingface.co/datasets/espnet/yodas3.

Introduction Welcome to MLAAD: The Multi-Language Audio Anti-Spoofing Dataset -- a dataset to train, test and evaluate audio deepfake detection. See the paper for more information. License MLAAD is published strictly for non-commercial academic research use, under the CC-BY-NC 4.0 license. Commercial use is not permitted. Download the dataset Option 1: Hugging Face datasets library Install the datasets package: pip install… See the full description on the dataset page: https://huggingface.co/datasets/mueller91/MLAAD.

This dataset contains 1,613,875 novel entries published on Royal Road.

Rosetta Activations Updated: 2026-06-15 02:30 UTC Contrastive activation extractions for 17 semantic concepts across 46 language models, supporting cross-architecture mechanistic interpretability research. Companion concept pair corpus: jamesrahenry/Rosetta_Concept_Pairs Papers: forthcoming Dataset Structure Rosetta-Activations/ ├── rcp_v1/ # Current extraction line — richest data (N≈2000) │ └── {Model_Name}/ │ ├── calibration_{concept}.npy… See the full description on the dataset page: https://huggingface.co/datasets/james-ra-henry/Rosetta-Activations.

Boasting over 13,000 hours of cumulative data and 5 million+ clips, it ranks as the largest open-source embodied intelligence dataset in the industry. Update Notes：Stage 3 data upload completed. 13,000+ hours of pure dual-hand data with frame-level alignment latency < 1ms Full high-precision trajectory reconstruction, breaking the limit of superficial open source, fully ready-to-use 3,000+ contributors and 10,000+ real household scenarios with exceptional diversity Comprehensive… See the full description on the dataset page: https://huggingface.co/datasets/genrobot2025/10Kh-RealOmin-OpenData.

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.