Instructions to use ProbeX/Model-J__SupViT__model_idx_0586 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_0586 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_0586") 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_0586") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0586") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5517e159e4283c21c2ed095b7224458478038347e4aec68c46b816d4002f5897
- Size of remote file:
- 5.37 kB
- SHA256:
- d531a15ebe4113b07bf79a7754003d73751d153f8efe2f1292e35ee7b2f0534a
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