Instructions to use mikerol/beta14-ViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikerol/beta14-ViT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mikerol/beta14-ViT") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("mikerol/beta14-ViT") model = AutoModelForImageClassification.from_pretrained("mikerol/beta14-ViT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06e32b6da1ce0426ab4571a70275e7ac84a17bda09de354c756607831b0cd7dd
- Size of remote file:
- 5.84 kB
- SHA256:
- 39b83d2a1de937fbd9abc3ca4ae63faa0ae6db3b1de6edd600fa78c1d6a0015a
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