Instructions to use mikerol/beta3-ViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikerol/beta3-ViT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mikerol/beta3-ViT") 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("mikerol/beta3-ViT") model = AutoModelForImageClassification.from_pretrained("mikerol/beta3-ViT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c30a6359b0ad58fb65ec0cd341b5588a12b6885b32adfa2061d7b6fb5f1e6bd3
- Size of remote file:
- 5.84 kB
- SHA256:
- fd30f9c13c2752af04db07e47d1aaed88b357cd122616af258f9d296d93bc48c
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