Instructions to use ProbeX/Model-J__SupViT__model_idx_0971 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0971 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0971") 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("ProbeX/Model-J__SupViT__model_idx_0971") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0971") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4eee5168902199420a50a7fac885c24198cf62518fb651314d47f04d156c22d5
- Size of remote file:
- 5.37 kB
- SHA256:
- 5d1d0025901433b3351558c8b1d373fcb3cedf0aa7c3dee20eb1052580ce62dc
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