Instructions to use ProbeX/Model-J__SupViT__model_idx_0428 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_0428 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_0428") 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_0428") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0428") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6815594a7889774ba12a8c6538bfc06c58ca02cd86319ee03780d7e15729cced
- Size of remote file:
- 5.37 kB
- SHA256:
- 481183fe660ef0e9c09fa52d6e364f121026dc5ed6a1664bb025485900dca949
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