Instructions to use ProbeX/Model-J__SupViT__model_idx_0860 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_0860 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_0860") 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_0860") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0860") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6a4c4e7464239b369ae4329e753059a8a085200b76d7bdad2b49780901e8d95
- Size of remote file:
- 5.37 kB
- SHA256:
- 413d79e3990abf863227bfbf652136a11dbf4ae0fcb31979ca209f2240631d36
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