Instructions to use ProbeX/Model-J__SupViT__model_idx_0708 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_0708 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_0708") 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_0708") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0708", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88b9586913684d610322f6866694d2ea03caea62189ee36f54229ee3a8051549
- Size of remote file:
- 5.37 kB
- SHA256:
- 5da4f3d2eff803ce5032ad5ca7d0759e7e9020f8ffb0d4d8446a878b2e0b1cc2
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