Instructions to use ProbeX/Model-J__SupViT__model_idx_0593 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_0593 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_0593") 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_0593") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0593", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63063f4ef57dd5ca837efb00de2a5193b929a71dac22f83a72bab78a2ed9ba9d
- Size of remote file:
- 5.37 kB
- SHA256:
- d63023d7663435fb70528f5ca8198b126f65a33e5dbc10f19c1eca9daf862b43
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