vllm-omni/docs/user_guide/examples/offline_inference/ltx2.md

LTX-2 Text-To-Video

Source https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inference/ltx2.

The Lightricks/LTX-2 pipeline generates high-quality videos from text prompts using a 19B parameter DiT architecture. It supports up to 4K video generation with synchronized audio.

Local CLI Usage

python text_to_video.py \
  --prompt "A panda riding a bicycle through a forest, cinematic lighting" \
  --height 512 \
  --width 768 \
  --num_frames 121 \
  --num_inference_steps 40 \
  --guidance_scale 4.0 \
  --output ltx2_output.mp4

Key arguments:

• --prompt: Text description of the video to generate (string).
• --height/--width: Output resolution (defaults 512x768). Dimensions must be divisible by 32.
• --num_frames: Number of frames (should be 8*n+1, e.g., 25, 81, 121). Default is 121.
• --guidance_scale: Classifier-free guidance scale (default: 4.0). Range 3.0-5.0 recommended.
• --negative_prompt: Optional text describing what to avoid in the video.
• --num_inference_steps: Number of denoising steps (default: 40).
• --seed: Random seed for reproducibility (default: 42).
• --fps: Frames per second for the saved MP4 (default: 24).
• --output: Path to save the generated video.

Example materials

??? abstract "text_to_video.py" py --8<-- "examples/offline_inference/ltx2/text_to_video.py"

??? abstract "text_to_video.md" md --8<-- "examples/offline_inference/ltx2/text_to_video.md"