Instructions to use ProbeX/Model-J__SupViT__model_idx_0929 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_0929 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_0929") 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_0929") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0929") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd0916cc97cf578b07e083af6c955690cc8d798113e7b65fbc9439fac79d5e42
- Size of remote file:
- 5.37 kB
- SHA256:
- 056f0f2a3a2fbdcaf0558453128338cc8cb3c952c90e6e48fe3090ae003cf41a
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