Instructions to use DEVAIEXP/SUPIR_Q with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DEVAIEXP/SUPIR_Q with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DEVAIEXP/SUPIR_Q", 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:
- 102122eee45bbec6fbe75e3f7742a9ce00c79305236d3aec1232d0fffb91bdfb
- Size of remote file:
- 132 MB
- SHA256:
- 1293cd3987c38638a0753a7a0a7d5a246f5686bbea40bd7e01146d4a8d22f935
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