Instructions to use hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageToImage processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution") model = AutoModelForImageToImage.from_pretrained("hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3782941ebcff3986174c27461fe1b5d70e894a361c67b786c49f65913e607f94
- Size of remote file:
- 767 kB
- SHA256:
- 28740923fdbdce35bdd3db8923ea2a75cc3458b7323dad16290bc0939f1a0263
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