Instructions to use ProbeX/Model-J__SupViT__model_idx_0275 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_0275 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_0275") 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_0275") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0275") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ad35cc58e55aa77b0615c370afa49bf1d284ea088397700ddfe78a54aee9c80
- Size of remote file:
- 5.37 kB
- SHA256:
- 15393c15e2f4ce0072e5beee9b2b7eb9a30662d4660a00c7a8061c05110fbd9f
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