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JLB-JLB
/
Model_folder

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Community
2

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

  • Libraries
  • Transformers

    How to use JLB-JLB/Model_folder with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="JLB-JLB/Model_folder")
    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("JLB-JLB/Model_folder")
    model = AutoModelForImageClassification.from_pretrained("JLB-JLB/Model_folder")
  • Notebooks
  • Google Colab
  • Kaggle
Model_folder
343 MB
Ctrl+K
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  • 1 contributor
History: 15 commits
JLB-JLB's picture
JLB-JLB
Model save
5824a19 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    1.99 kB
    Model save over 2 years ago
  • all_results.json
    403 Bytes
    Training in progress, step 30 over 2 years ago
  • config.json
    799 Bytes
    Training in progress, step 30 over 2 years ago
  • eval_results.json
    215 Bytes
    🍻 cheers over 2 years ago
  • preprocessor_config.json
    327 Bytes
    Training in progress, step 30 over 2 years ago
  • pytorch_model.bin
    343 MB
    xet
    Model save over 2 years ago
  • train_results.json
    208 Bytes
    Training in progress, step 30 over 2 years ago
  • trainer_state.json
    3.3 kB
    Training in progress, step 30 over 2 years ago
  • training_args.bin
    4.54 kB
    xet
    Training in progress, step 30 over 2 years ago