Instructions to use ProbeX/Model-J__SupViT__model_idx_0306 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_0306 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_0306") 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_0306") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0306") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9540ef49a40ba63c1304df0c576849f989f2939ef08a45eb92cd9a31741bb4ab
- Size of remote file:
- 5.37 kB
- SHA256:
- 8921f60298413c69aa25b581fa5d919f05358480b61f950239f24bba0159b869
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