Instructions to use ProbeX/Model-J__SupViT__model_idx_0497 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_0497 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_0497") 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_0497") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0497") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac7c986361872850171f3a0d94e3fd252346b84c5d205596ff9fc4b4c4fa0f35
- Size of remote file:
- 5.37 kB
- SHA256:
- 1b01dd6fd83694cac7d20ed96511c576405fcfe348ff04a94702396edf17b40f
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