vllm-omni/docs/user_guide/examples/offline_inference/text_to_image.md

Qwen-Image Offline Inference

Source https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inference/text_to_image.

This folder provides two simple entrypoints for experimenting with Qwen/Qwen-Image Tongyi-MAI/Z-Image-Turbo using vLLM-Omni:

• text_to_image.py: command-line script for single image generation.
• web_demo.py: lightweight Gradio UI for interactive prompt/seed/CFG exploration.

Local CLI Usage

python text_to_image.py \
  --model Tongyi-MAI/Z-Image-Turbo \
  --prompt "a cup of coffee on the table" \
  --seed 42 \
  --cfg_scale 4.0 \
  --num_images_per_prompt 1 \
  --num_inference_steps 50 \
  --height 1024 \
  --width 1024 \
  --output outputs/coffee.png

Key arguments:

• --prompt: text description (string).
• --seed: integer seed for deterministic sampling.
• --cfg_scale: true CFG scale (model-specific guidance strength).
• --num_images_per_prompt: number of images to generate per prompt (saves as output, output_1, ...).
• --num_inference_steps: diffusion sampling steps (more steps = higher quality, slower).
• --height/--width: output resolution (defaults 1024x1024).
• --output: path to save the generated PNG.

Web UI Demo

Launch the gradio demo:

python gradio_demo.py --port 7862

Then open http://localhost:7862/ on your local browser to interact with the web UI.

Example materials

??? abstract "gradio_demo.py" py --8<-- "examples/offline_inference/text_to_image/gradio_demo.py" ??? abstract "text_to_image.py" py --8<-- "examples/offline_inference/text_to_image/text_to_image.py"