Instructions to use ProbeX/Model-J__SupViT__model_idx_0876 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_0876 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_0876") 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_0876") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0876") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dc45c9f3ad185c375dd41d266608804e3d83702595832e4f82381c4c24d2249
- Size of remote file:
- 5.37 kB
- SHA256:
- a5f926b84551a07b3f618a26b6a63277fc4ab0c0d9de8a735ac82534e4200d3e
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