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MaxP
/
vit-base-riego

Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

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

  • Libraries
  • Transformers

    How to use MaxP/vit-base-riego with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="MaxP/vit-base-riego")
    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("MaxP/vit-base-riego")
    model = AutoModelForImageClassification.from_pretrained("MaxP/vit-base-riego")
  • Notebooks
  • Google Colab
  • Kaggle
vit-base-riego / runs
189 kB
Ctrl+K
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  • 2 contributors
History: 44 commits
MaxP's picture
MaxP
Model save
65bc59a about 3 years ago
  • Dec30_19-12-45_99208a1bd131
    Model save over 3 years ago
  • Mar09_21-41-37_dac6e29581bd
    Training in progress, step 100 about 3 years ago
  • Mar09_21-48-06_dac6e29581bd
    Model save about 3 years ago
  • Mar10_14-06-55_f6df06b64d4a
    Model save about 3 years ago
  • Mar10_20-57-01_a4c3c39bee63
    Model save about 3 years ago
  • Mar10_21-05-02_a4c3c39bee63
    Model save about 3 years ago