Instructions to use microsoft/beit-base-patch16-224-pt22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/beit-base-patch16-224-pt22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/beit-base-patch16-224-pt22k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, BeitForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("microsoft/beit-base-patch16-224-pt22k") model = BeitForMaskedImageModeling.from_pretrained("microsoft/beit-base-patch16-224-pt22k") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7bf5154458a8b9d6ad0d991faf0de22c68956979611afb14f263483fdcd2263b
- Size of remote file:
- 368 MB
- SHA256:
- 18b08989cad41adba4900055a11899c5d28b1d22b1fd5198c126eb2007ea000e
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