Instructions to use MagicBooth/mush with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MagicBooth/mush with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MagicBooth/mush", torch_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:
- 8abd0f1ed17634f232fcb4ef19b33b00aa543434c50e7b9df9a6f7aa5c0705ec
- Size of remote file:
- 681 MB
- SHA256:
- 9be5dccd8d284080e6f8510d801b135e82e6815488e16292bf1fb87cbb5df901
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.