Instructions to use ProbeX/Model-J__SupViT__model_idx_0177 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_0177 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_0177") 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_0177") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0177") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aabe1bff94dd9f9af4b2ef92bd1f8a1cb0a6e361421d94a9e9a7717943b79d25
- Size of remote file:
- 5.37 kB
- SHA256:
- 781b44f6d6b00e6d19a1e479ead4c673844cf921f27bba8902262045869b60ee
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