Instructions to use nitrosocke/mo-di-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nitrosocke/mo-di-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("nitrosocke/mo-di-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
- Draw Things
- DiffusionBee
- Xet hash:
- f11f5d9476f63a18cd63c6467e2b5d772dd28064f18846882455d721ca32ab6a
- Size of remote file:
- 492 MB
- SHA256:
- 5e1b47028db842e6e622e709aba2cf8d6e9a13d6d577c2c5cf3f45ee662344da
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