Instructions to use g349/vera with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use g349/vera 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("g349/vera") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/ComfyUI_7BQ8_4096_00001_bpzyg_1771150898.jpg
text: '-'
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: vera
vera

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