Instructions to use ProbeX/Model-J__SupViT__model_idx_0332 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_0332 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_0332") 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_0332") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0332") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3950522c77ff98b15414334133b0afbcacd6a43570ad721e4c6361c3d11e333
- Size of remote file:
- 5.37 kB
- SHA256:
- be46e8d8c7ff4dcf6b4625b8e8de3031eda3344ed13a4fe99f0b117799e16709
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