Instructions to use ProbeX/Model-J__SupViT__model_idx_0201 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_0201 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_0201") 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_0201") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0201") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf577e87af4b8bb0ae1df26b112c23dd69b0168f7e8a9e9a1f0e5bd4edae9a93
- Size of remote file:
- 5.37 kB
- SHA256:
- 2eaf4b15fe862237b41de38fc564990df30a21d4663d1ef91333eabe2440558b
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