Instructions to use stablediffusionapi/mix9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/mix9 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/mix9", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 3766013dadd6cee211a6d1ef2f1b10b8cf5f05b942548e7d827a8d3508e2c852
- Size of remote file:
- 167 MB
- SHA256:
- 66e3cbb82285af6a9e44298f8b0276d69bc084c5d31499302f4af096993c1eb4
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