Instructions to use ProbeX/Model-J__SupViT__model_idx_0487 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_0487 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_0487") 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_0487") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0487") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c70775234bf12af2d87e925246b4a90fb3fb632e1fd88da624db02be00b679d4
- Size of remote file:
- 5.37 kB
- SHA256:
- 7f1603ee9175dbd2deaa4c790460722c7e72e7299eabfdcea79b485f25e751f3
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