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MamaPearl
/
nula-cifar10-robust-v0

Image Classification
Transformers
Safetensors
nula
computer-vision
cnn
cifar10
adversarial-robustness
stress-test
downsampling
anti-aliasing
custom_code
Model card Files Files and versions
xet
Community

Instructions to use MamaPearl/nula-cifar10-robust-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use MamaPearl/nula-cifar10-robust-v0 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="MamaPearl/nula-cifar10-robust-v0", trust_remote_code=True)
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # Load model directly
    from transformers import AutoModelForImageClassification
    model = AutoModelForImageClassification.from_pretrained("MamaPearl/nula-cifar10-robust-v0", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
nula-cifar10-robust-v0
20.9 MB
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  • 1 contributor
History: 199 commits
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MamaPearl
Update README.md
61daecf verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 6 months ago
  • LICENSE
    1.07 kB
    Create LICENSE 6 months ago
  • README.md
    10.5 kB
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  • augmentations.py
    2.65 kB
    Update augmentations.py 6 months ago
  • config.json
    1.03 kB
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  • configuration_nula.py
    3.09 kB
    Update configuration_nula.py 6 months ago
  • dataset_nula.py
    2.9 kB
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  • evaluate.py
    2.84 kB
    Update evaluate.py 6 months ago
  • infer.py
    1.62 kB
    Update infer.py 5 months ago
  • model.safetensors
    20.9 MB
    xet
    Upload folder using huggingface_hub 6 months ago
  • modeling_nula.py
    6.43 kB
    Update modeling_nula.py 5 months ago
  • preprocessor_config.json
    317 Bytes
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  • robust_results.json
    813 Bytes
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  • train.py
    4.21 kB
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  • train_robust.py
    5.6 kB
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