Instructions to use ProbeX/Model-J__SupViT__model_idx_0223 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_0223 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_0223") 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_0223") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0223") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73980351f437c8fdcdca8d5cac6582d5251c7b882fb5ac2e3522f36d547b817d
- Size of remote file:
- 5.37 kB
- SHA256:
- 89b9e633e60dabc4e157c4bf6a00cbe9ce8560e0bb18880f69f9c43b7bec5907
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