Instructions to use cvmil/swin-base-patch4-window7-224_augmented-v2_tl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cvmil/swin-base-patch4-window7-224_augmented-v2_tl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="cvmil/swin-base-patch4-window7-224_augmented-v2_tl") 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("cvmil/swin-base-patch4-window7-224_augmented-v2_tl") model = AutoModelForImageClassification.from_pretrained("cvmil/swin-base-patch4-window7-224_augmented-v2_tl") - Notebooks
- Google Colab
- Kaggle
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