Instructions to use ProbeX/Model-J__SupViT__model_idx_0233 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_0233 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_0233") 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_0233") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0233") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9841c3a758d1e679a3f28cb39049093c7ffdb3fd7531e4abe6fbaf7467407aa1
- Size of remote file:
- 5.37 kB
- SHA256:
- ccda19fd33142a363e090d9f4c93ec3a28204da4ca687d1ec0063f29dc7f7511
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