Instructions to use ProbeX/Model-J__SupViT__model_idx_0757 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_0757 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_0757") 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_0757") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0757") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5c040cd948ffa1a29355bfde24b689d117275b75392270f60dfd9ad0687b9b0
- Size of remote file:
- 343 MB
- SHA256:
- 709c86082a4a2aee8e6117ae42162648b556567e26c08e121e8f05c97b60d00c
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