Instructions to use ProbeX/Model-J__SupViT__model_idx_0721 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_0721 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_0721") 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_0721") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0721") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7964d9329f51fa290d3f52f5d399de9c71c6ea12e7c43bebadb7b84406bfb6b
- Size of remote file:
- 343 MB
- SHA256:
- b3451e02f02a99c1b8e90e1726c488ccdc2485b3257e6972a62cb07307f1d45f
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