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GGital
/
vit-SUPER02

Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use GGital/vit-SUPER02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use GGital/vit-SUPER02 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="GGital/vit-SUPER02")
    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("GGital/vit-SUPER02")
    model = AutoModelForImageClassification.from_pretrained("GGital/vit-SUPER02")
  • Notebooks
  • Google Colab
  • Kaggle
vit-SUPER02
1.21 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 60 commits
GGital's picture
GGital
Model save
835d007 verified over 2 years ago
  • runs
    Model save over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    5.47 kB
    Model save over 2 years ago
  • config.json
    1.35 kB
    Training in progress, step 100 over 2 years ago
  • model.safetensors
    1.21 GB
    xet
    Training in progress, step 3200 over 2 years ago
  • preprocessor_config.json
    325 Bytes
    Training in progress, step 100 over 2 years ago
  • training_args.bin
    4.73 kB
    xet
    Training in progress, step 100 over 2 years ago