Instructions to use ProbeX/Model-J__SupViT__model_idx_0390 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_0390 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_0390") 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_0390") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0390") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d49fbc5a2cfca305ba0f470eef589b8c676bf89c478965a0dd7d4e0830161f78
- Size of remote file:
- 5.37 kB
- SHA256:
- cb84541cb8abe761ac0a3adbfee871fa15dfcb54bf3c18b2fc498372b3ba9580
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