Instructions to use ProbeX/Model-J__SupViT__model_idx_0392 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_0392 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_0392") 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_0392") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0392", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5ed557c56474871ec3d3e2b72180a497ad700612692498a85bf873cc5bfdb27
- Size of remote file:
- 5.37 kB
- SHA256:
- a23bdcfb309f32da8f28834414e078508af5ae178914cc44bb57ce56caa3d6af
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