Instructions to use udg/yesmi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use udg/yesmi with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("udg/yesmi", 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:
- 9495c6879d077a84e7938ba7c073219e52e3b14f2a8345df36bb5e9fd6fed134
- Size of remote file:
- 492 MB
- SHA256:
- 0f8ec5eea7931777456bac15bd07624595e3b9796557e82b473c34385b0f0455
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.