Instructions to use takutan/mo_w with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use takutan/mo_w with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("takutan/mo_w") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/content (1).jpeg
text: '-'
- output:
url: images/content.jpeg
text: '-'
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: mo_woman
license: apache-2.0
mo_w
.jpeg)
- Prompt
- -

- Prompt
- -
Trigger words
You should use mo_woman to trigger the image generation.
Download model
Download them in the Files & versions tab.