Instructions to use ProbeX/Model-J__SupViT__model_idx_0561 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_0561 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_0561") 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_0561") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0561") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfad354d9f9d1ea578bf4111ec1a27dc3aa525ae68ff3eeb5881a662045505d6
- Size of remote file:
- 5.37 kB
- SHA256:
- 07acd7c9a9fd8b50ede34c75e106e6a93113a2e855e9cdf031a26435344dd05a
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