Instructions to use ProbeX/Model-J__SupViT__model_idx_0549 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_0549 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_0549") 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_0549") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0549") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a878578f7f876cfc117b899c47fc3eba2575ed89b03d1e23c1055c1bf574f9d
- Size of remote file:
- 5.37 kB
- SHA256:
- 6d19c7884f20885b7bb5ce54f6165a3030c70ba751ad8b5e116932714bf80e3e
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