Instructions to use ProbeX/Model-J__SupViT__model_idx_0324 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_0324 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_0324") 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_0324") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0324") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 069e4e077fa7522900e75892046a87054864e508bbf7f8a9b7f96923c5c23711
- Size of remote file:
- 5.37 kB
- SHA256:
- 80ffa7feae6bcbb43b777ab7f104a34419bceb60fb01ed00ad3e1efa0b93976f
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