Instructions to use congruency/MOSS-Image-Turbo-MFD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use congruency/MOSS-Image-Turbo-MFD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("congruency/MOSS-Image-Turbo-MFD", 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
v0.1 seems to display stylistic drift towards smooth 2D art
#1
by V33rGeer - opened
Bottom Text
nice to see this again!
specific examples include not-quite-smooth 2D art, such as this;
https://civitai.red/models/2628760/simon-bisley-style
for some reason I insist on using https://huggingface.co/akhaliq/MOSS-Image-SFT-4-steps as a backbone, not sure why but anyway
Interesting! I'm not training on any illustrations. Right now the dataset is all safe for work, random, real life images. I'll add some art to the mix and hopefully that experience will add more illustrative detail on the next run


