Instructions to use microsoft/beit-large-patch16-224-pt22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/beit-large-patch16-224-pt22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/beit-large-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-large-patch16-224-pt22k") model = BeitForMaskedImageModeling.from_pretrained("microsoft/beit-large-patch16-224-pt22k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55d42d512daff8544b1e78a7740801e85a2b00a4ceb11dcf755af6b6ced7526f
- Size of remote file:
- 1.25 GB
- SHA256:
- ed81d0faf9f905c2eeee043a77976f997f9249c6fcda57172660ffb48a88d939
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