vllm-omni/examples/omni

Omni Examples

Examples showcasing multi-stage AR + DiT pipelines powered by vLLM-omni.

AR ➜ DiT with Diffusers Backend

# Optional: customise models
export AR_MODEL=Qwen/Qwen3-0.6B
export DIT_MODEL=./models/stable-diffusion-2-1/

# Run with defaults (20 steps @ 512x512)
python examples/omni/ar_dit_diffusers.py

# Faster run
python examples/omni/ar_dit_diffusers.py --steps 14 --height 384 --width 384 --guidance 4.5

Arguments:

• --ar-model: Override AR stage model (default Qwen/Qwen3-0.6B).
• --dit-model: Override DiT stage model (default env DIT_MODEL, else diffusers repo).
• --steps: Number of diffusion steps (default 20).
• --guidance: Guidance scale (default 5.0).
• --height / --width: Output resolution (default 512).
• --seed: Optional RNG seed.
• --prompt, --temperature, --max-tokens: Control AR stage generation.
• --output: Destination path for the generated image file.

Generated images are saved next to the script as omni_dit_output.png by default.

See the script for additional tweaks (scheduler, prompt chaining, etc.).