Instructions to use ProbeX/Model-J__SupViT__model_idx_0668 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_0668 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_0668") 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_0668") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0668") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 07a5f3eb49a22d269e69fd77f2496abe8607931f4ef2f0c4b00e684468e5a691
- Size of remote file:
- 5.37 kB
- SHA256:
- 37eb0f36aba9a1850c0054acfefca6dcf6dd5a2a0466191d14c3281c65d22fa7
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