Instructions to use Attonos/MRA_coder_local with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Attonos/MRA_coder_local 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("Attonos/MRA_coder_local") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/7d9a0f58-4b3d-4895-9b55-20e4efdcdc37.png
text: '-'
- output:
url: images/EXZO6789.PNG
text: '-'
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: null
license: apache-2.0
Edna_systems

- Prompt
- -
- Prompt
- -
Model description
Download model
Download them in the Files & versions tab.
