Instructions to use ProbeX/Model-J__SupViT__model_idx_0277 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_0277 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_0277") 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_0277") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0277") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70acc69c8bad7d8527dd265bd670ccc54ee764ae1b14648b52f9cca75c9c91c6
- Size of remote file:
- 5.37 kB
- SHA256:
- 5889c9987969b00d78f8e1a7e1aeb4e994ca996284aafc528befe0943179cc2b
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