Instructions to use ProbeX/Model-J__SupViT__model_idx_0539 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_0539 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_0539") 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_0539") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0539") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc523a840c17f3b9a862e3281eb1ae8fb2f8d826220f90d04668c51440192e1c
- Size of remote file:
- 5.37 kB
- SHA256:
- 3ce918a75cb30a183b75a18153caeb98962b992888081735f54c123ad9f79915
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