Instructions to use ProbeX/Model-J__SupViT__model_idx_0912 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_0912 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_0912") 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_0912") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0912") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fd058ea60bbb5e06cbe4624e18aad6999d15a41db3daa1ec7859871e4bc9333
- Size of remote file:
- 5.37 kB
- SHA256:
- 3f3e0da2300f2a6c210e3250e08d86e7412920aa1f33fa4bb3d842867894f3b3
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