Instructions to use ProbeX/Model-J__SupViT__model_idx_0867 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_0867 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_0867") 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_0867") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0867", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b78ed3c3a3b17bdf02df09a1c761349ad532223af3226f7f83adc2ddad3b4e4e
- Size of remote file:
- 5.37 kB
- SHA256:
- f55ea1b832c42f20ca60ebfefd55a98145a8dd3d96d3b1f7f5f0413437b5f3d7
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