Instructions to use ProbeX/Model-J__SupViT__model_idx_0589 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_0589 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_0589") 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_0589") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0589", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa12eed77c07e1ef9ce2a2ba851429b9c77f16026b929e9c66a3558f679e8e25
- Size of remote file:
- 5.37 kB
- SHA256:
- fefb47dbcb9a550e8bfd70597ea9d91f2580e8daaccfb1ee2bb3cad18f63b0fc
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