Instructions to use nateraw/resnet50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nateraw/resnet50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nateraw/resnet50") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nateraw/resnet50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7780fcd1fdc612426566d8072f820b9d45f5514c7d529dbb4a1c0095a2bc4083
- Size of remote file:
- 103 MB
- SHA256:
- 1936f5bb6a13a12c1a281297cf26150a2e32df750d872b2ba79dd31f1ad2ccfc
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