Instructions to use ProbeX/Model-J__SupViT__model_idx_0921 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_0921 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_0921") 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_0921") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0921") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0849a05182992a73d8df7bacabac2e1d141cb9f13a7401c3f7dbb4bbfea04c54
- Size of remote file:
- 343 MB
- SHA256:
- e77e6c1e046c25d3ff3b5767a1710ce72733e0b7eb717897e114a38fdb466db1
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