Instructions to use ShinnosukeU/parameter_v9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ShinnosukeU/parameter_v9 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_v9", 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:
- 19693c22dece7e45a8084d4129d016691a35ceb845c1cb6ab93a153c303a7392
- Size of remote file:
- 3.44 GB
- SHA256:
- 486ce19f67df7532f999cfa2d5e321e056b95ee0418daacc6a20ca62a35e3886
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