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tzhao3
/
vit-L-CIFAR10

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

Instructions to use tzhao3/vit-L-CIFAR10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tzhao3/vit-L-CIFAR10 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="tzhao3/vit-L-CIFAR10")
    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-CIFAR10")
    model = AutoModelForImageClassification.from_pretrained("tzhao3/vit-L-CIFAR10", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
vit-L-CIFAR10
4.85 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
39004c9 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 3 years ago
  • config.json
    991 Bytes
    Upload 8 files about 3 years ago
  • model.safetensors
    1.21 GB
    xet
    Adding `safetensors` variant of this model over 1 year ago
  • optimizer.pt
    2.43 GB
    xet
    Upload 8 files about 3 years ago
  • preprocessor_config.json
    325 Bytes
    Upload 8 files about 3 years ago
  • pytorch_model.bin
    1.21 GB
    xet
    Upload 8 files about 3 years ago
  • rng_state.pth
    14.6 kB
    xet
    Upload 8 files about 3 years ago
  • scheduler.pt
    627 Bytes
    xet
    Upload 8 files about 3 years ago
  • trainer_state.json
    2.4 kB
    Upload 8 files about 3 years ago
  • training_args.bin
    3.9 kB
    xet
    Upload 8 files about 3 years ago