Instructions to use ProbeX/Model-J__SupViT__model_idx_0672 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_0672 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_0672") 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_0672") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0672") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eacb475b6606b8d336dfb16d6be7f148b82db96e00aad7175989444155081c26
- Size of remote file:
- 5.37 kB
- SHA256:
- 3ea4f75f52fb787b26108caa314f6a11a6c1e01376fb8a0fb32ca39d4fbe2490
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