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miladfa7
/
Model-Kaggle-Product-ViT-V1

Image Classification
Transformers
PyTorch
vit
Model card Files Files and versions
xet
Community
1

Instructions to use miladfa7/Model-Kaggle-Product-ViT-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use miladfa7/Model-Kaggle-Product-ViT-V1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="miladfa7/Model-Kaggle-Product-ViT-V1")
    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("miladfa7/Model-Kaggle-Product-ViT-V1")
    model = AutoModelForImageClassification.from_pretrained("miladfa7/Model-Kaggle-Product-ViT-V1")
  • Notebooks
  • Google Colab
  • Kaggle
Model-Kaggle-Product-ViT-V1
1.03 GB
Ctrl+K
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  • 1 contributor
History: 2 commits
miladfa7's picture
miladfa7
upload new model checkpoint
f4ff3f5 about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • config.json
    957 Bytes
    upload new model checkpoint about 3 years ago
  • optimizer.pt
    687 MB
    xet
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  • preprocessor_config.json
    325 Bytes
    upload new model checkpoint about 3 years ago
  • pytorch_model.bin
    343 MB
    xet
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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
    1.87 kB
    upload new model checkpoint about 3 years ago
  • training_args.bin
    3.58 kB
    xet
    upload new model checkpoint about 3 years ago