Instructions to use ShinnosukeU/parameter_v22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShinnosukeU/parameter_v22 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ShinnosukeU/parameter_v22", 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:
- 02911ae360ade06edb2648bb09618589aab394a66a1f6f57dcd367ba7e555e65
- Size of remote file:
- 492 MB
- SHA256:
- 37fe5b177014b643db995b5dfac6169d8fe85746498d622c0f1b61418d62455e
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