Instructions to use ProbeX/Model-J__SupViT__model_idx_0779 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_0779 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_0779") 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_0779") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0779") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a14a40bf864e6c6c953757de0ab6effe6a0bce23bdcbf993a6e8af4f9d302031
- Size of remote file:
- 5.37 kB
- SHA256:
- c7602d447b169e2c7637196c338038db5784b38913081e52da2fc5719d73da58
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