Instructions to use ProbeX/Model-J__SupViT__model_idx_0792 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_0792 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_0792") 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_0792") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0792") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63b59ead098f7717bf36ed8361785d84ef3c53a1b00c68a402956bb8bd026a37
- Size of remote file:
- 5.37 kB
- SHA256:
- 8aed1d13f7fc2a7e5fa65d1258aaaa5681244c002cf50bc75e5d5393e764e2e1
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