Instructions to use ecgoing/Izumi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ecgoing/Izumi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ecgoing/Izumi", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 032edd8327506fed2ae55fe3f0e8e1fe5af8b851c40647967673552332c30326
- Size of remote file:
- 492 MB
- SHA256:
- 88dbacd6c02da4dc30d054cf9462daa07d420a232b2ad58298219aaf78be5806
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