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:
- ace390867a7babdb5b8c068c79d871937d52a05fe5cc257859702add6ebf83f0
- Size of remote file:
- 3.44 GB
- SHA256:
- f1dff8edb50b24653fd84cb3fa78e0f70d08cad7dd61d575692f2ba06a83f677
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