Instructions to use Luuu01/RESNET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Luuu01/RESNET with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Luuu01/RESNET") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Luuu01/RESNET") model = AutoModelForImageClassification.from_pretrained("Luuu01/RESNET") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e0a8a2c45bb72f46d48afccc2b21f3b0785bf25232a6d4935d6dba0fcd81563
- Size of remote file:
- 94.5 MB
- SHA256:
- 550ce242ef31772092de00992a5f979cd27fe71e1bce8bfd62def121fed157bb
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