Instructions to use mwalmsley/resnet18-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use mwalmsley/resnet18-test with timm:
import timm model = timm.create_model("hf-hub:mwalmsley/resnet18-test", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mwalmsley/resnet18-test: direct link, hf CLI and curl.
- Browser
- Download file 46.8 MB
-
https://huggingface.co/mwalmsley/resnet18-test/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mwalmsley/resnet18-test/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mwalmsley/resnet18-test/resolve/main/pytorch_model.bin
46.8 MB
- Xet hash:
- 66d4881124d9abbeec87aa660eeb69aaf9535e27601739241dbcce2821e00899
- Size of remote file:
- 46.8 MB
- SHA256:
- a6d9e2056298c59451503845494f28eacb03a7596854d5e10079c34d0e8906b9
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