Instructions to use ProbeX/Model-J__SupViT__model_idx_0401 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_0401 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_0401") 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_0401") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0401") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d781962db5ca02891f45e44db8786bfd8cb78efc38f37b5438a569544087ace0
- Size of remote file:
- 5.37 kB
- SHA256:
- d496492dfd76d0e9f7d32b211df5d02cbae8e88ed61c4d8d492e21043afc34a2
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