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[Feature] Add official LTX multimodal guidance and precision guard (#5148)

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Signed-off-by: mglyn <1203789601@qq.com>
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Mu GuanLin authored and GitHub committed 2026-07-28 10:44:25 +00:00
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docs/user_guide/examples/offline_inference/image_to_video.md
+7 -19
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@@ -4,7 +4,7 @@ Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inf
This example demonstrates how to generate videos from images using Wan2.2,
LTX-2/LTX-2.3, and HunyuanVideo-1.5 Image-to-Video models with vLLM-Omni's
LTX-2, and HunyuanVideo-1.5 Image-to-Video models with vLLM-Omni's
offline inference API.
## Local CLI Usage
@@ -53,34 +53,22 @@ python image_to_video.py \
--output i2v_output.mp4
```
### LTX-2.3
### LTX-2
```bash
python image_to_video.py \
--model diffusers/LTX-2.3-Diffusers \
--model-class-name LTX23ImageToVideoPipeline \
--model Lightricks/LTX-2 \
--image cherry_blossom.jpg \
--prompt "Cherry blossoms swaying gently in the breeze with synchronized ambient sound" \
--negative-prompt "worst quality, inconsistent motion, blurry, jittery, distorted" \
--height 384 \
--width 512 \
--num-frames 25 \
--guidance-scale 4.0 \
--num-inference-steps 20 \
--frame-rate 24 \
--fps 24 \
--output ltx23_i2v_output.mp4
--output ltx2_i2v_output.mp4
```
Use the Diffusers-format checkpoint `diffusers/LTX-2.3-Diffusers`; the
upstream `Lightricks/LTX-2.3` raw safetensors repo is not directly loadable by
this pipeline. Pass `--model-class-name LTX23ImageToVideoPipeline` to select
the LTX-2.3 image-to-video pipeline.
See the [LTX-2 recipe](../../../../recipes/LTX/LTX-2.md) for all checkpoints,
pipeline selection, T2V, defaults, and advanced options.
Key arguments:
- `--model`: Model ID (I2V-A14B for MoE, TI2V-5B for unified T2V+I2V, or
LTX-2/LTX-2.3).
- `--model`: Model ID (I2V-A14B for MoE, TI2V-5B for unified T2V+I2V, or LTX-2).
- `--image`: Path to input image (required).
- `--prompt`: Text description of desired motion/animation.
- `--height/--width`: Output resolution (auto-calculated from image if not set).
docs/user_guide/examples/offline_inference/text_to_video.md
+8 -38
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@@ -12,7 +12,7 @@ For backend selection and SageAttention usage, see the [Diffusion Attention Back
| Model | Default Resolution | Default Frames | Default Steps | Guidance | VRAM (BF16) |
|---|---|---|---|---|---|
| `Wan-AI/Wan2.2-T2V-A14B-Diffusers` | 720x1280 | 81 | 40 | 4.0 | ~60 GiB |
| `diffusers/LTX-2.3-Diffusers` | 384x512 | 25 | 20 | 4.0 | 96GB-class GPU |
| `Lightricks/LTX-2` | 512x768 | 121 | 40 | video 3.0 / audio 7.0 | Model-dependent |
| `hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-480p_t2v` | 480x832 | 121 | 50 | 6.0 | 1×A100 80GB |
| `hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-720p_t2v` | 720x1280 | 121 | 50 | 6.0 | FP8 + VAE tiling required |
@@ -35,45 +35,17 @@ python text_to_video.py \
--output t2v_out.mp4
```
LTX2 example:
### LTX-2
```bash
python text_to_video.py \
--model "Lightricks/LTX-2" \
--prompt "A cinematic close-up of ocean waves at golden hour." \
--negative-prompt "worst quality, inconsistent motion, blurry, jittery, distorted" \
--height 512 \
--width 768 \
--num-frames 121 \
--num-inference-steps 40 \
--guidance-scale 4.0 \
--frame-rate 24 \
--output ltx2_out.mp4
```
### LTX-2.3
```bash
python text_to_video.py \
--model diffusers/LTX-2.3-Diffusers \
--model-class-name LTX23Pipeline \
--model Lightricks/LTX-2 \
--prompt "Cherry blossoms swaying gently in the breeze with synchronized ambient sound" \
--negative-prompt "worst quality, inconsistent motion, blurry, jittery, distorted" \
--height 384 \
--width 512 \
--num-frames 25 \
--num-inference-steps 20 \
--guidance-scale 4.0 \
--frame-rate 24 \
--fps 24 \
--audio-sample-rate 48000 \
--output ltx23_t2v_output.mp4
--output ltx2_output.mp4
```
Use the Diffusers-format checkpoint `diffusers/LTX-2.3-Diffusers`; the
upstream `Lightricks/LTX-2.3` raw safetensors repo is not directly loadable by
this pipeline. Pass `--model-class-name LTX23Pipeline` to select the LTX-2.3
text-to-video pipeline explicitly.
See the [LTX-2 recipe](../../../../recipes/LTX/LTX-2.md) for all checkpoints,
pipeline selection, I2V, defaults, and advanced options.
### HunyuanVideo-1.5 (480p)
@@ -135,8 +107,7 @@ python text_to_video.py \
### Common
- `--model`: Diffusers model ID or local path.
- `--model-class-name`: Optional explicit pipeline class. Use `LTX23Pipeline`
for LTX-2.3 text-to-video.
- `--model-class-name`: Optional explicit pipeline override.
- `--prompt`: text description (string).
- `--height/--width`: output resolution. Default depends on model.
- `--num-frames`: number of frames. Default depends on model.
@@ -151,8 +122,7 @@ python text_to_video.py \
- `--enable-cpu-offload`: enable CPU offloading for diffusion models.
- `--enable-layerwise-offload`: enable layerwise offloading on DiT modules.
- `--frame-rate`: generation FPS for pipelines that require it (e.g., LTX2).
- `--audio-sample-rate`: audio sample rate for embedded audio (when the
pipeline returns audio; LTX-2.3 outputs 48kHz audio).
- `--audio-sample-rate`: fallback audio sample rate when the pipeline returns audio.
- `--quantization`: quantization method (`fp8` for FP8, `gguf` for GGUF).
- `--flow-shift`: scheduler flow_shift parameter.