Instructions to use predictia/cerra_denoise_convswin2sr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use predictia/cerra_denoise_convswin2sr with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("predictia/cerra_denoise_convswin2sr", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 522f3010b13bebc387bc6edc128c3c96e6ce6ca397ff13bea49a97f9b18d9236
- Size of remote file:
- 33.7 MB
- SHA256:
- 7ec41140d4babe4554941dd9b20bccae89d8de3eabc4217579373113da158984
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