Instructions to use ProbeX/Model-J__SupViT__model_idx_0115 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_0115 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_0115") 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_0115") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0115", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d279dc48d3cb3d386c9b172f16462f7a9b61e1a7d25f1c49bf327f8bbc10e111
- Size of remote file:
- 5.37 kB
- SHA256:
- 12dee808ee2c3858ed7deb3d7f446726486b5eb3c42630ae344bee4ec9da6414
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