Instructions to use mitchtech/cardassian-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mitchtech/cardassian-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mitchtech/cardassian-diffusion", 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:
- ae27c2d769c83089cd90a53b0045d69fc27f42394a95a0e1a9ac5bbd0760dfc0
- Size of remote file:
- 492 MB
- SHA256:
- 083e21b5acb39112e133a447f06ef79968443376f834dbb15965b8ae88fd535c
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