Instructions to use ProbeX/Model-J__SupViT__model_idx_0469 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_0469 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_0469") 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_0469") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0469") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1ee2374a267b9de2d0fae83bd351420590ac869418c50d600086f447343a25c
- Size of remote file:
- 5.37 kB
- SHA256:
- 96c96a7265a24e4298297df16049888aa4f9ea5f4c32a426f3bc37e62dae85b2
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