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buildborderless
/
CommunityForensics-DeepfakeDet-ViT

Image Classification
Transformers
Safetensors
timm
vit
detection
deepfake
forensics
deepfake_detection
community
opensight
Model card Files Files and versions
xet
Community
3

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")
  • 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
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

add "do_center_crop": true to preprocessor_config.json

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#3 opened 2 months ago by
xieofxie
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