Instructions to use ProbeX/Model-J__SupViT__model_idx_0086 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_0086 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_0086") 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_0086") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0086") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cad7e5893277147a68a245c41b4cb712ebb1e8911d656725a1a9e7628184545
- Size of remote file:
- 5.37 kB
- SHA256:
- 7ce0fb2c3e4efd4b55d393f5a6cf1340f413817aa3b2059d8e996fa8ef69d748
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