Instructions to use ProbeX/Model-J__SupViT__model_idx_0518 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_0518 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_0518") 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_0518") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0518") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 402aa1bd3d494365ff9ad5a3d596cc7805da3da02b16ff0149b957b62ec15052
- Size of remote file:
- 5.37 kB
- SHA256:
- f819438a9cd0459bdab7f8aaaabe697ab7a336ac3bef36da9a878b18ec6608a6
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