Instructions to use ProbeX/Model-J__SupViT__model_idx_0718 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_0718 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_0718") 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_0718") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0718") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e94d53a1c5f48d166ccab7b7d5d5cd4e86a5a6add40acf50fd1c73aa96046e32
- Size of remote file:
- 5.37 kB
- SHA256:
- b6270f84d8fc25bf8599326e9da03cddbbae1f685cb8636375a045a0eb5a6dd9
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