[Refactor] Unify the LTX-2 and LTX-2.3 pipeline runtime (#5147)

Signed-off-by: mglyn <1203789601@qq.com>

docs/user_guide/examples/offline_inference/image_to_video.md

@@ -57,7 +57,7 @@ python image_to_video.py \
 
 ```bash
 python image_to_video.py \
-  --model dg845/LTX-2.3-Diffusers \
+  --model diffusers/LTX-2.3-Diffusers \
   --model-class-name LTX23ImageToVideoPipeline \
   --image cherry_blossom.jpg \
   --prompt "Cherry blossoms swaying gently in the breeze with synchronized ambient sound" \
@@ -72,7 +72,7 @@ python image_to_video.py \
   --output ltx23_i2v_output.mp4
 ```
 
-Use a Diffusers-format checkpoint such as `dg845/LTX-2.3-Diffusers`; the
+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.

docs/user_guide/examples/offline_inference/text_to_video.md

@@ -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 |
-| `dg845/LTX-2.3-Diffusers` | 384x512 | 25 | 20 | 4.0 | 96GB-class GPU |
+| `diffusers/LTX-2.3-Diffusers` | 384x512 | 25 | 20 | 4.0 | 96GB-class GPU |
 | `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 |
 
@@ -55,7 +55,7 @@ python text_to_video.py \
 
 ```bash
 python text_to_video.py \
-  --model dg845/LTX-2.3-Diffusers \
+  --model diffusers/LTX-2.3-Diffusers \
   --model-class-name LTX23Pipeline \
   --prompt "Cherry blossoms swaying gently in the breeze with synchronized ambient sound" \
   --negative-prompt "worst quality, inconsistent motion, blurry, jittery, distorted" \
@@ -70,7 +70,7 @@ python text_to_video.py \
   --output ltx23_t2v_output.mp4
 ```
 
-Use a Diffusers-format checkpoint such as `dg845/LTX-2.3-Diffusers`; the
+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.

docs/user_guide/examples/online_serving/text_to_video.md

@@ -13,6 +13,7 @@ This example demonstrates how to deploy text-to-video models for online video ge
 | Wan2.1 T2V (14B) | `Wan-AI/Wan2.1-T2V-14B-Diffusers` |
 | Wan2.2 T2V | `Wan-AI/Wan2.2-T2V-A14B-Diffusers` |
 | LTX-2 | `Lightricks/LTX-2` |
+| LTX-2.3 | `diffusers/LTX-2.3-Diffusers` |
 
 ## Wan2.2 T2V
 
@@ -374,6 +375,17 @@ curl -sS -X POST http://localhost:8098/v1/videos \
   -F "seed=42"
 ```
 
+## LTX-2.3
+
+LTX-2.3 uses a Diffusers-format checkpoint and a dedicated pipeline class:
+
+```bash
+vllm serve diffusers/LTX-2.3-Diffusers --omni --port 8098 \
+    --model-class-name LTX23Pipeline
+```
+
+Send requests through the same `/v1/videos` API shown in the LTX-2 example.
+
 ## Example materials
 
 ??? abstract "response.json"