Instructions to use ProbeX/Model-J__SupViT__model_idx_0081 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_0081 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_0081") 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_0081") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0081") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5323d1243869d873274068463141d9ae639da701d4a3bddfe2d967b64e814755
- Size of remote file:
- 5.37 kB
- SHA256:
- c4787d217fb15acc9c85ed5a23b6bd3cab520379b3b2101ea6fb2386dac27830
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