Instructions to use caidas/swin2SR-classical-sr-x4-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caidas/swin2SR-classical-sr-x4-64 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-image" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-image", model="caidas/swin2SR-classical-sr-x4-64")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageToImage processor = AutoImageProcessor.from_pretrained("caidas/swin2SR-classical-sr-x4-64") model = AutoModelForImageToImage.from_pretrained("caidas/swin2SR-classical-sr-x4-64", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from caidas/swin2SR-classical-sr-x4-64: direct link, hf CLI and curl.
- Browser
- Download file 49.2 MB
-
https://huggingface.co/caidas/swin2SR-classical-sr-x4-64/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://caidas/swin2SR-classical-sr-x4-64/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/caidas/swin2SR-classical-sr-x4-64/resolve/main/pytorch_model.bin
49.2 MB
- Xet hash:
- 5b6d7ab60553ff7702e941fceb49fa4db7ca102483e5518979df54c7b3da58ee
- Size of remote file:
- 49.2 MB
- SHA256:
- d173b005e999ce79e07b71b7f208922d40176b4039785f7d7bb0b641d9a85dee
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