Instructions to use ProbeX/Model-J__SupViT__model_idx_0772 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_0772 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_0772") 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_0772") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0772") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37d94cdd024e15f170dd95fbaf7f17b2964c84a92cebbd08dac8c2cd0d67bc60
- Size of remote file:
- 5.37 kB
- SHA256:
- 7489cec3147b7edc83cf465999bb04e6ea52a2ffb486ff65088c8f47e19ce2cb
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