Instructions to use kenobi/SDO_VT1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kenobi/SDO_VT1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kenobi/SDO_VT1") 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("kenobi/SDO_VT1") model = AutoModelForImageClassification.from_pretrained("kenobi/SDO_VT1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8741abc67e3f1e88b32f994272a4f40bbef5cb97b504b4daaf00f0be1ab1fbc4
- Size of remote file:
- 343 MB
- SHA256:
- 310b3c17baf2bcf441b392ee269f22f11cde8a43be3d28f53e77e7146b862df7
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