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:
- de8b10d609c834a892c555a8ebc822a809faf4db4effccfa305cf395ea942fc1
- Size of remote file:
- 62.2 MB
- SHA256:
- 7a9b7d6ac9062b92da9b44f61ace8c62da76ce86fb0947fdb40fb449792e194a
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