Instructions to use microsoft/beit-large-patch16-224-pt22k-ft22k 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-ft22k 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-ft22k") 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("microsoft/beit-large-patch16-224-pt22k-ft22k") model = AutoModelForImageClassification.from_pretrained("microsoft/beit-large-patch16-224-pt22k-ft22k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c46d6aeeef9035f7c02aa8da53071321a26aa938612eaf4cd0b3f0ae8b94b1c5
- Size of remote file:
- 1.31 GB
- SHA256:
- 4738128e25b85f1a4a33a868f24e3c7dc691af65fb1473b472a05d130b1e84e7
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