Instructions to use ProbeX/Model-J__SupViT__model_idx_0621 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_0621 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_0621") 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_0621") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0621") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca4512b2b063da5129ed8aa90262de02aa15d95a13c37544e205a56f28b89b9f
- Size of remote file:
- 343 MB
- SHA256:
- 5509944caec2fecffd4ce6bfb53ab01532b0b46361182e8fb86235df5df4f29a
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