Model Details
Full Model IDnphSi/Z-Image-Lora
Pipeline / Tasktext-to-image
Librarydiffusers
Downloads (all-time)240.7K
Likes131
Last Modified7/26/2026
Author / OrgnphSi
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-to-image", model="nphSi/Z-Image-Lora")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
diffuserstext-to-imagelorasafetensorsz-imagebase_model:Tongyi-MAI/Z-Imagebase_model:adapter:Tongyi-MAI/Z-Imagelicense:apache-2.0region:us
More Text to Image Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🎨 Task: Text to Image
This model is designed for the Text to Image task. Explore more models for this use case.
All Text to Image Models →📊 Popularity
⬇ Downloads240.7K
❤️ Community Likes131
🛠️ Requirements
- →Install: pip install diffusers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.