Instructions to use microsoft/swin-base-patch4-window12-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swin-base-patch4-window12-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/swin-base-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-base-patch4-window12-384") model = AutoModelForImageClassification.from_pretrained("microsoft/swin-base-patch4-window12-384") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88e2930785bd71c2a9631833e97e2a4de946e7a912eba31adbf33dfd427bee50
- Size of remote file:
- 356 MB
- SHA256:
- bd484fab3574d16df27d67c5004e2fb303e7c59e4aad7cda1819d2e949ee7ca0
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