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:
- e9505d6f50f2e778f4e1540387d2e8140293007f91f8a1a218151a5e6452a8b9
- Size of remote file:
- 102 MB
- SHA256:
- c0b29e2ac563332d02274d6d656379d3b0957b91b7c8b6c1b4433657d74d6e68
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