Instructions to use flax/mo-di-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use flax/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("flax/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:
- 3bce0ee8e146621b1f9bfda31fc3ef273f7a7a0630518e5f6aa3a01e4fb69a83
- Size of remote file:
- 3.44 GB
- SHA256:
- 5623ddd7ac3600bbd014b8cb5241a6b48fd46708ef737b8fd3574086543e4e83
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