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
| { | |
| "crop_size": 32, | |
| "do_pad": true, | |
| "do_rescale": true, | |
| "image_processor_type": "Swin2SRImageProcessor", | |
| "pad_size": 8, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": 32 | |
| } | |