Instructions to use ProbeX/Model-J__SupViT__model_idx_0159 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_0159 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_0159") 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_0159") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0159") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ccb66baf87df64ad26ebcb8461390fa0fef222fdb542e1aadba4992e7e194e6
- Size of remote file:
- 5.37 kB
- SHA256:
- 4d712b85032915ac539c206fd71c71ecdafce5f6efd56fc1a23b7037d7db41b4
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