Instructions to use ProbeX/Model-J__SupViT__model_idx_0926 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_0926 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_0926") 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_0926") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0926") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35af2bce078c49364a7ab8bf77114ef501ca3a06253308129e4539da5b5f1760
- Size of remote file:
- 5.37 kB
- SHA256:
- 277fee61b2a621e459d70b5618c8893c713cf93be8afe22f19739385424d2969
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