Instructions to use nphSi/Z-Image-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nphSi/Z-Image-Lora 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,Tongyi-MAI/Z-Image-Turbo", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("nphSi/Z-Image-Lora") prompt = "Alexandra Chando (vrtlAlexandraChando)" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Slide of Sina Tkotsch was made with ZIT Int8 ConvRot
#54
by nphSi - opened
Quality is on par with Q8 but twice the speed. Its only a bit faster than mxfp8 but much better quality.
Definitively a recommendation for VRam retards like me.
https://huggingface.co/Winnougan/Z-Image-Base-Turbo-INT8-Convrot/tree/main
- You need to switch to nightly in Comfy-Manager for native support of Int8
Quick demo workflow with prompt enhancer / TE combo. Uses https://github.com/knishika62/ComfyUI-TextGenerateQwen3Prompt

