Instructions to use frgfm/resnet18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frgfm/resnet18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="frgfm/resnet18") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("frgfm/resnet18", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2452ca68f9553ec86ce544f6e1f35d591ede28d8c98c721501b20a2347fb21c7
- Size of remote file:
- 44.8 MB
- SHA256:
- 55c7a7da52f54264858a5138824f871af6b68f7779d3f4a1661997ecadd2687b
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