Instructions to use ProbeX/Model-J__SupViT__model_idx_0669 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_0669 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_0669") 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_0669") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0669", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2efde7094f8b81543b8a25ad9492b0691a0fc02fc72754bf8e97367d9f9bc9e5
- Size of remote file:
- 5.37 kB
- SHA256:
- 23b1da3665a945fdb3f014ca8ab7c2da2a77ad00df2f387bdb24854fcd68b557
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