Instructions to use edadaltocg/resnet18_cifar10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use edadaltocg/resnet18_cifar10 with timm:
import timm model = timm.create_model("hf_hub:edadaltocg/resnet18_cifar10", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from edadaltocg/resnet18_cifar10: direct link, hf CLI and curl.
- Browser
- Download file 44.8 MB
-
https://huggingface.co/edadaltocg/resnet18_cifar10/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://edadaltocg/resnet18_cifar10/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/edadaltocg/resnet18_cifar10/resolve/main/pytorch_model.bin
44.8 MB
- Xet hash:
- 5b2767bd0f8fb4473221302dc36f8903ceda476a769e6e385c8077e88cfd5223
- Size of remote file:
- 44.8 MB
- SHA256:
- f656242526b567dbd46857276acbcfcb4ee74a7f8a7ae5e56557b7e8fa5d914a
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