Instructions to use ProbeX/Model-J__SupViT__model_idx_0337 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_0337 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_0337") 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_0337") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0337") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b61e5c245b3f26215610fbca1ed5b307ce229ffbf180a8e4d7e4b7988e48d02
- Size of remote file:
- 5.37 kB
- SHA256:
- e1509c1046f3946398463464e3c30a12433dc45f5da94d5c14dbbf973e582a9e
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