Instructions to use ProbeX/Model-J__SupViT__model_idx_0719 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_0719 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_0719") 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_0719") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0719") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3804607823e9972e5a1f1fb482cdb933ec55b8bb1146103e2082b1759fb4ff0
- Size of remote file:
- 5.37 kB
- SHA256:
- 401b28f3b84687138e008f251be2b862f645a48a50be0688771c7ed0df04dbaa
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