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t1msan
/
ViT_generated_or_not

Image Classification
Transformers
Safetensors
vit
Model card Files Files and versions
xet
Community

Instructions to use t1msan/ViT_generated_or_not with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use t1msan/ViT_generated_or_not with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="t1msan/ViT_generated_or_not")
    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("t1msan/ViT_generated_or_not")
    model = AutoModelForImageClassification.from_pretrained("t1msan/ViT_generated_or_not")
  • Notebooks
  • Google Colab
  • Kaggle
ViT_generated_or_not / checkpoint-550
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  • 1 contributor
History: 1 commit
t1msan's picture
t1msan
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0e37833 verified about 2 years ago
  • config.json
    720 Bytes
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  • model.safetensors
    343 MB
    xet
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  • optimizer.pt
    687 MB
    xet
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  • preprocessor_config.json
    578 Bytes
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  • rng_state.pth
    14.6 kB
    xet
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  • scheduler.pt
    627 Bytes
    xet
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  • trainer_state.json
    12.6 kB
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  • training_args.bin
    4.41 kB
    xet
    Upload folder using huggingface_hub about 2 years ago