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Download README.md from MIT-OL-AI-D/cifar-10-python: direct link, hf CLI and curl.
- Browser
- Download file 879 Bytes
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https://huggingface.co/datasets/MIT-OL-AI-D/cifar-10-python/resolve/main/README.md
- Command line
-
hf download hf://datasets/MIT-OL-AI-D/cifar-10-python/README.md
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curl -L -o README.md https://huggingface.co/datasets/MIT-OL-AI-D/cifar-10-python/resolve/main/README.md
879 Bytes
metadata
license: unknown
pretty_name: CIFAR-10 (original python archive)
task_categories:
- image-classification
CIFAR-10, original python archive
Unmodified copy of cifar-10-python.tar.gz from https://www.cs.toronto.edu/~kriz/cifar.html,
mirrored so course notebooks do not depend on the original host.
- MD5
c58f30108f718f92721af3b95e74349a(the valuetorchvision.datasets.CIFAR10checks) - 170,498,071 bytes
Use with torchvision
Set the URL before the first datasets.CIFAR10(...) call. torchvision still verifies the
MD5, so nothing else changes. Pin a commit hash from this repo's history, not main.
datasets.CIFAR10.url = ("https://huggingface.co/datasets/MIT-OL-AI-D/cifar-10-python/"
"resolve/<commit>/cifar-10-python.tar.gz")
Citation
Alex Krizhevsky, Learning Multiple Layers of Features from Tiny Images, 2009.