Instructions to use microsoft/swin-large-patch4-window12-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swin-large-patch4-window12-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/swin-large-patch4-window12-384") 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/swin-large-patch4-window12-384") model = AutoModelForImageClassification.from_pretrained("microsoft/swin-large-patch4-window12-384", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 900927018846532cc3fad1737c748cc0985471544f5aaca49db479483f9140af
- Size of remote file:
- 788 MB
- SHA256:
- 4632705e6d9f26aec307856ec6e0874ed81c4a88eff4c0da97e5003a3fda3828
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