Instructions to use ProbeX/Model-J__SupViT__model_idx_0753 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_0753 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_0753") 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_0753") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0753") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ac7853ff59423b8230cccff3983934de9601cb3cd29a892e53e15db832934ed
- Size of remote file:
- 5.37 kB
- SHA256:
- 304f05d594ad7f7d0730d2236303819d5d7abb1c271eba14f62e4067134fb00f
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