Instructions to use ProbeX/Model-J__SupViT__model_idx_0919 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_0919 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_0919") 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_0919") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0919") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- acb40761389232fa82b972e60cb61056fbd4eafd5605af0460210491f70904b4
- Size of remote file:
- 5.37 kB
- SHA256:
- 4a64ca223c6d51d6262e1c020939b185cf5b9260442600b9f7c617f8df6cc420
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