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 resnet-50.pt from hvlgo/resnet18: direct link, hf CLI and curl.
- Browser
- Download file 94.5 MB
-
https://huggingface.co/hvlgo/resnet18/resolve/main/resnet-50.pt
- Command line
-
hf download hf://hvlgo/resnet18/resnet-50.pt
-
curl -L -o resnet-50.pt https://huggingface.co/hvlgo/resnet18/resolve/main/resnet-50.pt
94.5 MB
- Xet hash:
- 5d18e0ad755722b7fcd247f7108cd8808df3cef2b45db4d75b51ed1ae70977fd
- Size of remote file:
- 94.5 MB
- SHA256:
- 7a169b7144817c06e25174bc2fb3325392b95b8a9b11f37afe06ecff81d396c5
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