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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62d6a15eff0ff3422ac83e33dc305a59cbaa2ed0d9d51ac2561450a706a2a06d
- Size of remote file:
- 793 kB
- SHA256:
- 0855edb4cc549b3f25bcc5ce23d248aa9ee4ee9bc272235f6ad6373940d1b835
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