Instructions to use microsoft/swin-base-patch4-window7-224-in22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/swin-base-patch4-window7-224-in22k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="microsoft/swin-base-patch4-window7-224-in22k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("microsoft/swin-base-patch4-window7-224-in22k") model = AutoModelForImageClassification.from_pretrained("microsoft/swin-base-patch4-window7-224-in22k", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin with git-lfs
Browse files- pytorch_model.bin +3 -0
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