Instructions to use ProbeX/Model-J__SupViT__model_idx_0570 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_0570 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_0570") 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_0570") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0570", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6a70716c7c9be1da6ca92932608fd17c482d48395d9c6693162f6336ba7ebf1
- Size of remote file:
- 5.37 kB
- SHA256:
- f4d4271cfe35e57cdae0dbca5cb1d4ac05885094442e5ac0e75db804aaa1aebf
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