Instructions to use jays009/Restnet50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jays009/Restnet50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jays009/Restnet50") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jays009/Restnet50", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8da1e4e8c2bb15b77e8fba7afa306912ba0ec493f789683b720c28cb03d924ae
- Size of remote file:
- 94.4 MB
- SHA256:
- bf3fcb2885dcd8c9f19df562bf751f5506747ebbe2d134f4a704a6dcd450e5f0
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