Instructions to use ProbeX/Model-J__SupViT__model_idx_0359 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_0359 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_0359") 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_0359") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0359") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10468068f3fac173eea297f4a0e03bcd5082e096c5bc87a83a4746c876bdd28f
- Size of remote file:
- 5.37 kB
- SHA256:
- d305c3c7a42d204f0eec99b8d45c0f7a559a920210e6452702761b85f4e307ee
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