NOTICE: 7/22/2026 Ungated again. Friendly reminder to all to please respect the MIT license. Attribution should be made to the original project (see bottom) as well as this repository. Other than that, you're free to use the model as you wish. Trained on 2.7M samples across 4,803 generators (see Training Data) Model presented in Community Forensics: Using Thousands of Generators to Train Fake Image Detectors. Uploaded for community validation as part of OpenSight An upcoming open source framework for adaptive deepfake detection. Project OpenSight HF Spaces coming soon with an eval playground and eventually a leaderboard. Preview: Model Details Model Description Vision Transformer (ViT) model trained on the largest dataset to date for detecting AI generated images in forensic applications. Developed by: Jeongsoo Park and Andrew Owens, University of Michigan Model type: Vision Transformer (ViT Small) License: MIT (compatible with CreativeML OpenRAIL M referenced in [2411.04125v1.pdf]) Finetuned from: timm/vit small patch16 384.augreg in21k ft in1k Adapted for HF inference compatibility by Borderless. HF Space will be open sourced shortly showcasing various ways to run ultra fast infe…
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