Instructions to use hvlgo/resnet18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hvlgo/resnet18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hvlgo/resnet18")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hvlgo/resnet18") model = AutoModel.from_pretrained("hvlgo/resnet18", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __trial_0.pt from hvlgo/resnet18: direct link, hf CLI and curl.
- Browser
- Download file 87.3 kB
-
https://huggingface.co/hvlgo/resnet18/resolve/main/__trial_0.pt
- Command line
-
hf download hf://hvlgo/resnet18/__trial_0.pt
-
curl -L -o __trial_0.pt https://huggingface.co/hvlgo/resnet18/resolve/main/__trial_0.pt
87.3 kB
- Xet hash:
- ebbe9a078a6607dacff14b9e54da0824727a430d3c721e08882b7bbf5d934b7d
- Size of remote file:
- 87.3 kB
- SHA256:
- c24a8959ca4faafb09d4c99db562db7fcc494b41a294b599d726c21f06ef3c91
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