Instructions to use ProbeX/Model-J__SupViT__model_idx_0439 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_0439 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_0439") 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_0439") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0439") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 393d2b2de8e57333f1b8e6ff70d9a46e4d62d0784fa63dd6e54762a8f9f29953
- Size of remote file:
- 5.37 kB
- SHA256:
- 73d9718612ccd38c1e506a89a6e82857c308a954365fc8128a7afb5c5d1d603d
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