Instructions to use ProbeX/Model-J__SupViT__model_idx_0754 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_0754 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_0754") 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_0754") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0754") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- deab08f6ef309dbb961579a28b5b3355c31e1781eeb196ac604ee8ae3a94e9bb
- Size of remote file:
- 5.37 kB
- SHA256:
- 42ba9ba5efeae08df516722026ac3b99405e62c91c4691a6a924a56b7067467a
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