Instructions to use ProbeX/Model-J__SupViT__model_idx_0519 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_0519 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_0519") 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_0519") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0519") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa417170b02af448dfa1ddeb733a0cdf3a8d6d2e0436cc8e1cc21eb5073c8775
- Size of remote file:
- 5.37 kB
- SHA256:
- 54a45b182cbdbcc42fca5042002c32483d898bbcd12ca2f9a944355f3068db1e
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