Instructions to use ProbeX/Model-J__SupViT__model_idx_0028 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_0028 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_0028") 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_0028") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0028") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b405ee55a073b76e5c654b0de2dfb9c9a8f9256e9618a4c9c0f6aa54582efe1c
- Size of remote file:
- 5.37 kB
- SHA256:
- 7aaa210547b764249a86f62cc3fdd7a0df7ca8a26d0c3d4a404d67a9d0eae6c4
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