Instructions to use caidas/swin2SR-classical-sr-x2-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caidas/swin2SR-classical-sr-x2-64 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="caidas/swin2SR-classical-sr-x2-64")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageToImage processor = AutoImageProcessor.from_pretrained("caidas/swin2SR-classical-sr-x2-64") model = AutoModelForImageToImage.from_pretrained("caidas/swin2SR-classical-sr-x2-64", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a20a13fd570dc0ac118f2781f2128087f26096bc9d9be7522a0e2ae2fffeb6ca
- Size of remote file:
- 48.6 MB
- SHA256:
- adf54cd2539bec31262ce6d6f97fea5079fcb8388bc7eaff0082c0dc0c87259c
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