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OmAlve
/
vit-base-pets

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

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

  • Libraries
  • Transformers

    How to use OmAlve/vit-base-pets with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="OmAlve/vit-base-pets")
    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("OmAlve/vit-base-pets")
    model = AutoModelForImageClassification.from_pretrained("OmAlve/vit-base-pets")
  • Notebooks
  • Google Colab
  • Kaggle
vit-base-pets / runs
62.6 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
OmAlve's picture
OmAlve
better evaluation and only trained the classifier layer
934882f verified about 2 years ago
  • Mar30_07-36-47_7ccd926a2ffc
    initialcommit about 2 years ago
  • Mar30_10-54-27_5905f67ec798
    added preprocessor about 2 years ago
  • Mar30_12-24-34_837f7dd663e8
    fixed labeling bug about 2 years ago
  • Mar31_10-44-13_0de03c5233fc
    better evaluation and only trained the classifier layer about 2 years ago