Instructions to use ProbeX/Model-J__SupViT__model_idx_0889 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_0889 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_0889") 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_0889") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0889") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfb05e9d64f8257f58fbba1041ff4a80661484a4e9e5d95b892639b80795acc9
- Size of remote file:
- 5.37 kB
- SHA256:
- 34ad7aafa85fe9e4b691a74ec7bb17503d0326cbaeaa6c6a7382667fcc2db6db
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