Instructions to use ProbeX/Model-J__SupViT__model_idx_0824 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_0824 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_0824") 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_0824") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0824") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba3bd45af4cf461ebc2c90cad7f6c15e7717635bc4eae4633acc556e5aab32b9
- Size of remote file:
- 5.37 kB
- SHA256:
- 2debc26438c095ab058b166946c51495cfc9955481c3eecdaff5abe3117ceff5
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