Instructions to use ProbeX/Model-J__SupViT__model_idx_0423 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_0423 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_0423") 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_0423") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0423", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c85726e65e3f147764045894673620ad3255ca45ff519fa61386ef49ebab2242
- Size of remote file:
- 5.37 kB
- SHA256:
- 839fb6611edd5c002b308b0880959288f3f1282869bebc89d5697c4ddfe75315
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