Instructions to use ProbeX/Model-J__SupViT__model_idx_0533 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_0533 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_0533") 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_0533") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0533") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd8ddb68ffca0edc2efcad723e3d9d0c1e9477e2522aa89e41506e7fbf1c4194
- Size of remote file:
- 5.37 kB
- SHA256:
- 509aa9a4da5c9a71f413ef78a55d30fba4648b4462aef3274c89bea172eb207b
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