Instructions to use microsoft/swinv2-large-patch4-window12-192-22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swinv2-large-patch4-window12-192-22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/swinv2-large-patch4-window12-192-22k") 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/swinv2-large-patch4-window12-192-22k") model = AutoModelForImageClassification.from_pretrained("microsoft/swinv2-large-patch4-window12-192-22k") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75598a84dbfb05c1f3379314bc541595b0c41b389126c75a8974abe197550b19
- Size of remote file:
- 915 MB
- SHA256:
- d2376131d369f0ac869aaff212cd9e5b748657186ba789172cc86f0991cbaaa3
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