Instructions to use ProbeX/Model-J__SupViT__model_idx_0087 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_0087 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_0087") 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_0087") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0087") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b9a55a14e8458acb02a35a72a941b9b96c1b57403fad016d5d2a739e7657627
- Size of remote file:
- 5.37 kB
- SHA256:
- 9875690bb84fe9ed8300bda0e37d6e0fa54954ee57d7b1a1bef4b2ff28455307
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