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:
- acc17f5ca9ae03c1528c8b54a7fdf60bf0ac0e9d6ac1a09821ea4c3f5229fd4c
- Size of remote file:
- 1.3 GB
- SHA256:
- 3975ce79d15612bdb285181c2ec621e1ec5f2f8e74e570f38b943ef89087098d
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