Instructions to use ProbeX/Model-J__SupViT__model_idx_0231 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_0231 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_0231") 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_0231") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0231") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69ec48de25dbef3855344238647454e9911896ab752a89f36abdd3f5c2a3f3d2
- Size of remote file:
- 5.37 kB
- SHA256:
- 7c0a68cc2a06891e0c2a2424b3bd7648be58739024d42f4e2807a358d94ef1d9
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