Instructions to use caidas/swin2SR-lightweight-x2-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caidas/swin2SR-lightweight-x2-64 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="caidas/swin2SR-lightweight-x2-64")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageToImage processor = AutoImageProcessor.from_pretrained("caidas/swin2SR-lightweight-x2-64") model = AutoModelForImageToImage.from_pretrained("caidas/swin2SR-lightweight-x2-64") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 519cbe176d6705decbc70d82618c674af6e8b0f4b8daca14b4b1a9ac1e9a6b7b
- Size of remote file:
- 4.18 MB
- SHA256:
- 9784753b51c4b93b87d53088b862c1961b04eaa69460463bed170d5c444b3d0b
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