Instructions to use rhazis/resnet18-random-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use rhazis/resnet18-random-classifier with timm:
import timm model = timm.create_model("hf-hub:rhazis/resnet18-random-classifier", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rhazis/resnet18-random-classifier: direct link, hf CLI and curl.
- Browser
- Download file 44.8 MB
-
https://huggingface.co/rhazis/resnet18-random-classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rhazis/resnet18-random-classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rhazis/resnet18-random-classifier/resolve/main/pytorch_model.bin
44.8 MB
- Xet hash:
- af47b8dcbcddfde2fb2b36de2b2fc16b0608df8742bc94f380c7fb3492fed9ad
- Size of remote file:
- 44.8 MB
- SHA256:
- 71b848484b5ee5a8439d0a8887bc51e2958a654447ce0661056a91583448cb9c
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