Instructions to use edadaltocg/resnet34_cifar10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use edadaltocg/resnet34_cifar10 with timm:
import timm model = timm.create_model("hf-hub:edadaltocg/resnet34_cifar10", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from edadaltocg/resnet34_cifar10: direct link, hf CLI and curl.
- Browser
- Download file 85.3 MB
-
https://huggingface.co/edadaltocg/resnet34_cifar10/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://edadaltocg/resnet34_cifar10/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/edadaltocg/resnet34_cifar10/resolve/main/pytorch_model.bin
85.3 MB
- Xet hash:
- ca6196f25cef9e18ee755b6fd1e661146b54e8f0e990a6478a7bb60df49a6bc1
- Size of remote file:
- 85.3 MB
- SHA256:
- 16de60d27d06f0e9170926f7fe68a94e8805b11a5718045de59c38dbf866b6cd
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