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miittnnss
/
sweets

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

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

  • Libraries
  • Transformers

    How to use miittnnss/sweets with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="miittnnss/sweets")
    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("miittnnss/sweets")
    model = AutoModelForImageClassification.from_pretrained("miittnnss/sweets")
  • Notebooks
  • Google Colab
  • Kaggle
sweets
343 MB
Ctrl+K
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  • 2 contributors
History: 2 commits
miittnnss's picture
miittnnss
commit files to HF hub
8451a3a over 2 years ago
  • images
    commit files to HF hub over 2 years ago
  • runs
    commit files to HF hub over 2 years ago
  • .gitattributes
    1.8 kB
    commit files to HF hub over 2 years ago
  • README.md
    891 Bytes
    commit files to HF hub over 2 years ago
  • config.json
    871 Bytes
    commit files to HF hub over 2 years ago
  • model.safetensors
    343 MB
    xet
    commit files to HF hub over 2 years ago
  • preprocessor_config.json
    327 Bytes
    commit files to HF hub over 2 years ago