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tzhao3
/
vit-L-FashionMNIST

Image Classification
Transformers
PyTorch
vit
Model card Files Files and versions
xet
Community
1

Instructions to use tzhao3/vit-L-FashionMNIST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tzhao3/vit-L-FashionMNIST with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="tzhao3/vit-L-FashionMNIST")
    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("tzhao3/vit-L-FashionMNIST")
    model = AutoModelForImageClassification.from_pretrained("tzhao3/vit-L-FashionMNIST", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
vit-L-FashionMNIST
3.64 GB
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  • 1 contributor
History: 2 commits
tzhao3's picture
tzhao3
Upload 8 files
531f71c almost 3 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • config.json
    1.03 kB
    Upload 8 files almost 3 years ago
  • optimizer.pt
    2.43 GB
    xet
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  • preprocessor_config.json
    325 Bytes
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  • pytorch_model.bin
    1.21 GB
    xet
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  • rng_state.pth
    15.6 kB
    xet
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  • scheduler.pt
    627 Bytes
    xet
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  • trainer_state.json
    2.6 kB
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  • training_args.bin
    3.45 kB
    xet
    Upload 8 files almost 3 years ago