Instructions to use ENOT-AutoDL/imagenet-benchmark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ENOT-AutoDL/imagenet-benchmark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ENOT-AutoDL/imagenet-benchmark") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ENOT-AutoDL/imagenet-benchmark", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7e1a1efbb6728c1cb73ac97054aca90fba53a9aca45846ebb0128e128e8a1ac
- Size of remote file:
- 20.9 MB
- SHA256:
- 387b705b1d83c844f513d7646f95138f8fcfb420e1ef0b5f8d7039e550c66b91
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