Instructions to use ProbeX/Model-J__SupViT__model_idx_0896 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_0896 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_0896") 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_0896") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0896") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b671ec8837022a5ff055f469df3560b7cc9360573d852723b30f7aae90ee48cb
- Size of remote file:
- 5.37 kB
- SHA256:
- 6aea4a663bb7a69bc340b893619d365dc208a3591490fa5d867a3f257b48adaf
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