Instructions to use ProbeX/Model-J__SupViT__model_idx_0089 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_0089 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_0089") 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_0089") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0089") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d36982690cecbaf420b1c2654a34c205deec66d4e0d606ab2148b7fcae039b7b
- Size of remote file:
- 5.37 kB
- SHA256:
- a2b303d619b70a994f12327546a61655765930d9e00088ce79f8e99359d4aa0e
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