Instructions to use ProbeX/Model-J__SupViT__model_idx_0695 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_0695 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_0695") 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_0695") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0695") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e17d6f2e05b84acf84890c7d6069260dc808e1d14799cc757d54a72c45e01301
- Size of remote file:
- 5.37 kB
- SHA256:
- 3ac0d5b5e7d3609cbe9fdabaa69b46c727324bc2fd893c3b25e791fc19f72b9f
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