Instructions to use ProbeX/Model-J__SupViT__model_idx_0502 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_0502 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_0502") 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_0502") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0502", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7210dec75022db32f90e67dcea461b1de1c032b6ccc2791d3fbdced2118a216f
- Size of remote file:
- 5.37 kB
- SHA256:
- 2f3a38c5d4f019d1c623ce62a979523a5d7ca0284605bc4e5d0415dde729defa
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