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:
- a78a644ff3dbad5c242c2f0fc53d386d5615f97e3e017a44c6ceb9cb7630716c
- Size of remote file:
- 3.44 GB
- SHA256:
- 64a02de2d346a0583d631d9debe80eed2218cdce42d1fb6fdcd8d2743c62e07d
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