Instructions to use ProbeX/Model-J__SupViT__model_idx_0749 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_0749 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_0749") 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_0749") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0749") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 020af4d1b66949ea61ed4e797c4bf457609345f372f76592eaee9597542c2de7
- Size of remote file:
- 5.37 kB
- SHA256:
- 57c92db1d0426bb2c024cc2bc90f9db28a6d973a4d66da88741874f10b5d644f
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