Instructions to use ProbeX/Model-J__SupViT__model_idx_0343 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_0343 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_0343") 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_0343") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0343") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17ae469fac692000731e14709ac9d8f865077a9244490549c94334fb4c6ad1bd
- Size of remote file:
- 5.37 kB
- SHA256:
- 11215cd96fd342f941da7fee0375c4dc31f3c5461b30938eb40e4aae08590fb5
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