Image Classification
Transformers
ONNX
Safetensors
timm
vit
detection
deepfake
forensics
deepfake_detection
community
opensight
Instructions to use buildborderless/CommunityForensics-DeepfakeDet-ViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use buildborderless/CommunityForensics-DeepfakeDet-ViT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="buildborderless/CommunityForensics-DeepfakeDet-ViT") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("buildborderless/CommunityForensics-DeepfakeDet-ViT") model = AutoModelForImageClassification.from_pretrained("buildborderless/CommunityForensics-DeepfakeDet-ViT", device_map="auto") - timm
How to use buildborderless/CommunityForensics-DeepfakeDet-ViT with timm:
import timm model = timm.create_model("hf_hub:buildborderless/CommunityForensics-DeepfakeDet-ViT", pretrained=True) - Inference
- Notebooks
- Google Colab
- Kaggle
docs: restore OpenSight community validation and preview sections
Browse files
README.md
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Vision Transformer (ViT-Small) trained on 2.7M samples across 4,803 generators for detecting AI-generated images. Presented in [Community Forensics: Using Thousands of Generators to Train Fake Image Detectors](https://huggingface.co/papers/2411.04125) (CVPR 2025).
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## IMPORTANT — Configuration Fix (July 2026)
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**If you downloaded this model before July 22, 2026, your local copy has incorrect config and weights.** Apologies for the mess — this model was originally hastily put together as an internal proof-of-concept for a hackathon, and we never imagined it would quietly become one of the top image classification models on Hugging Face. This update is long overdue.
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Vision Transformer (ViT-Small) trained on 2.7M samples across 4,803 generators for detecting AI-generated images. Presented in [Community Forensics: Using Thousands of Generators to Train Fake Image Detectors](https://huggingface.co/papers/2411.04125) (CVPR 2025).
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**Uploaded for community validation as part of OpenSight** — An upcoming open-source framework for adaptive deepfake detection.
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**Project OpenSight HF Spaces coming soon with an eval playground and eventually a leaderboard. Preview:**
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## IMPORTANT — Configuration Fix (July 2026)
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**If you downloaded this model before July 22, 2026, your local copy has incorrect config and weights.** Apologies for the mess — this model was originally hastily put together as an internal proof-of-concept for a hackathon, and we never imagined it would quietly become one of the top image classification models on Hugging Face. This update is long overdue.
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