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jjmcarrascosa
/
vit_receipts_classifier

Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community
2

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

  • Libraries
  • Transformers

    How to use jjmcarrascosa/vit_receipts_classifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="jjmcarrascosa/vit_receipts_classifier")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoImageProcessor, AutoModelForImageClassification
    
    processor = AutoImageProcessor.from_pretrained("jjmcarrascosa/vit_receipts_classifier")
    model = AutoModelForImageClassification.from_pretrained("jjmcarrascosa/vit_receipts_classifier", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
vit_receipts_classifier
5.15 GB
Ctrl+K
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  • 3 contributors
History: 7 commits
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