LTX-2.5 Integration

README.md

@@ -41,6 +41,8 @@ See also:
 
 > Currently, the development personnel of this project are limited, with most of the work handled by [Artiprocher](https://github.com/Artiprocher) and [mi804](https://github.com/mi804). Therefore, the progress of new feature development will be relatively slow, and the speed of responding to and resolving issues is limited. We apologize for this and ask developers to understand.
 
+- **September 10, 2026** We have integrated [LTX-2.5](https://modelscope.cn/models/Lightricks/LTX-2.5), the latest audio-video generation model from Lightricks. The features include text-to-audio/video with automatic duration prediction, image-to-audio/video with keyframe interpolation, audio-to-video, audio-video retake, IC-LoRA pixel spatial upscaling, text-to-audio, INT8 quantized inference, low VRAM inference, and training. For details, please refer to the [documentation](/docs/en/Model_Details/LTX-2.md) and [code](/examples/ltx2/).
+
 - **September 10, 2026** We have open-sourced [DiffSynth-ComfyUI](https://github.com/modelscope/DiffSynth-ComfyUI). Now you can run model inference with DiffSynth-Studio in [ComfyUI](https://github.com/Comfy-Org/ComfyUI).
 
 - **September 8, 2026** We trained a [MiniMax-H3 Training Adapter](https://www.modelscope.cn/models/DiffSynth-Studio/MiniMax-H3-TrainingAdapter) for the CFG-distilled MiniMax-H3 base, a DeCFG LoRA training adapter offered in FL2VA and Ref2VA versions. The training data comes from the self-generated [MiniMax-H3-Self-Generated-Dataset](https://www.modelscope.cn/datasets/DiffSynth-Studio/MiniMax-H3-Self-Generated-Dataset). Based on this adapter, we trained two toy models, [MiniMax-H3-Songyu-LoRA](https://www.modelscope.cn/models/mibei0804/MiniMax-H3-Songyu-LoRA) (character identity, FL2VA) and [MiniMax-H3-Ref2VA-FirstFrame-Lineart](https://www.modelscope.cn/models/mibei0804/MiniMax-H3-Ref2VA-FirstFrame-Lineart) (lineart first-frame control, Ref2VA), as references for inference and fine-tuning.
@@ -642,6 +644,16 @@ https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/59fb2f7b-8de0-44
 | JoyAI-Image | [jd-opensource/JoyAI-Image-Edit](https://modelscope.cn/models/jd-opensource/JoyAI-Image-Edit) | [code](/examples/joyai_image/model_inference/JoyAI-Image-Edit.py) | [code](/examples/joyai_image/model_inference_low_vram/JoyAI-Image-Edit.py) | [code](/examples/joyai_image/model_training/full/JoyAI-Image-Edit.sh) | [code](/examples/joyai_image/model_training/validate_full/JoyAI-Image-Edit.py) | [code](/examples/joyai_image/model_training/lora/JoyAI-Image-Edit.sh) | [code](/examples/joyai_image/model_training/validate_lora/JoyAI-Image-Edit.py) |
 | ERNIE-Image | [PaddlePaddle/ERNIE-Image](https://www.modelscope.cn/models/PaddlePaddle/ERNIE-Image) | [code](/examples/ernie_image/model_inference/ERNIE-Image.py) | [code](/examples/ernie_image/model_inference_low_vram/ERNIE-Image.py) | [code](/examples/ernie_image/model_training/full/ERNIE-Image.sh) | [code](/examples/ernie_image/model_training/validate_full/ERNIE-Image.py) | [code](/examples/ernie_image/model_training/lora/ERNIE-Image.sh) | [code](/examples/ernie_image/model_training/validate_lora/ERNIE-Image.py) |
 | ERNIE-Image | [PaddlePaddle/ERNIE-Image-Turbo](https://www.modelscope.cn/models/PaddlePaddle/ERNIE-Image-Turbo) | [code](/examples/ernie_image/model_inference/ERNIE-Image-Turbo.py) | [code](/examples/ernie_image/model_inference_low_vram/ERNIE-Image-Turbo.py) | — | — | — | — |
+| LTX-2.5 | [Lightricks/LTX-2.5: OneStagePipeline-T2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2AV-OneStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2AV-OneStage.py) | [code](/examples/ltx2/model_training/full/LTX-2.5-T2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_full/LTX-2.5-T2AV.py) | [code](/examples/ltx2/model_training/lora/LTX-2.5-T2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_lora/LTX-2.5-T2AV.py) |
+| LTX-2.5 | [Lightricks/LTX-2.5: TwoStagePipeline-T2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2AV-TwoStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2AV-TwoStage.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: OneStagePipeline-I2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-I2AV-OneStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-I2AV-OneStage.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: TwoStagePipeline-I2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-I2AV-TwoStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-I2AV-TwoStage.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: TwoStagePipeline-A2V](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-A2V-TwoStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-A2V-TwoStage.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: TwoStagePipeline-Retake](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2AV-TwoStage-Retake.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2AV-TwoStage-Retake.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: T2A](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2A.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2A.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: DistilledPipeline-T2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2AV-DistilledPipeline.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2AV-DistilledPipeline.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5-22b-IC-LoRA-Pixel-Spatial-Upscaler](https://www.modelscope.cn/models/Lightricks/LTX-2.5-22b-IC-LoRA-Pixel-Spatial-Upscaler) | [code](/examples/ltx2/model_inference/LTX-2.5-IC-LoRA-Pixel-Spatial-Upscaler.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-IC-LoRA-Pixel-Spatial-Upscaler.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: INT8-ConvRot](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2AV-INT8-ConvRot.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2AV-INT8-ConvRot.py) | - | - | - | - |
 | LTX-2 | [jd-opensource/JoyAI-Echo](https://modelscope.cn/models/jd-opensource/JoyAI-Echo) | [code](/examples/ltx2/model_inference/JoyAI-Echo-T2AV.py) | [code](/examples/ltx2/model_inference_low_vram/JoyAI-Echo-T2AV.py) | [code](/examples/ltx2/model_training/full/JoyAI-Echo-T2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_full/JoyAI-Echo-T2AV.py) | [code](/examples/ltx2/model_training/lora/JoyAI-Echo-T2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_lora/JoyAI-Echo-T2AV.py) |
 | LTX-2 | [Lightricks/LTX-2.3: OneStagePipeline-I2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.3) | [code](/examples/ltx2/model_inference/LTX-2.3-I2AV-OneStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.3-I2AV-OneStage.py) | [code](/examples/ltx2/model_training/full/LTX-2.3-I2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_full/LTX-2.3-I2AV.py) | [code](/examples/ltx2/model_training/lora/LTX-2.3-I2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_lora/LTX-2.3-I2AV.py) |
 | LTX-2 | [Lightricks/LTX-2.3: TwoStagePipeline-I2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.3) | [code](/examples/ltx2/model_inference/LTX-2.3-I2AV-TwoStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.3-I2AV-TwoStage.py) | - | - | - | - |

README_zh.md

@@ -41,6 +41,8 @@
 
 > 目前本项目的开发人员有限，大部分工作由 [Artiprocher](https://github.com/Artiprocher) 和 [mi804](https://github.com/mi804) 负责，因此新功能的开发进展会比较缓慢，issue 的回复和解决速度有限，我们对此感到非常抱歉，请各位开发者理解。
 
+- **2026年9月10日** 我们接入了 [LTX-2.5](https://modelscope.cn/models/Lightricks/LTX-2.5)，这是 Lightricks 最新的音视频联合生成模型。支持的功能包括自动时长预测的文生音视频、关键帧插值的图生音视频、音频驱动视频、音视频区域重生成、IC-LoRA 像素空间上采样、文生音频、INT8 量化推理、低显存推理以及模型训练。详情请参考[文档](/docs/zh/Model_Details/LTX-2.md)和[示例代码](/examples/ltx2/)。
+
 - **2026年9月10日** 我们开源了 [DiffSynth-ComfyUI](https://github.com/modelscope/DiffSynth-ComfyUI)，现在，你可以在 [ComfyUI](https://github.com/Comfy-Org/ComfyUI) 中使用 DiffSynth-Studio 运行模型推理了。
 
 - **2026年9月8日** 我们为 CFG 蒸馏的 MiniMax-H3 基座训练了 [MiniMax-H3 Training Adapter](https://www.modelscope.cn/models/DiffSynth-Studio/MiniMax-H3-TrainingAdapter)，这是一个 DeCFG LoRA 训练 Adapter，提供 FL2VA 与 Ref2VA 两个版本。训练数据来自自生成数据集 [MiniMax-H3-Self-Generated-Dataset](https://www.modelscope.cn/datasets/DiffSynth-Studio/MiniMax-H3-Self-Generated-Dataset)。基于该 Adapter，我们训练了两个 toy 模型，[MiniMax-H3-Songyu-LoRA](https://www.modelscope.cn/models/mibei0804/MiniMax-H3-Songyu-LoRA)（角色身份，FL2VA）与 [MiniMax-H3-Ref2VA-FirstFrame-Lineart](https://www.modelscope.cn/models/mibei0804/MiniMax-H3-Ref2VA-FirstFrame-Lineart)（线稿首帧控制，Ref2VA），供推理与微调参考。
@@ -603,6 +605,13 @@ https://github.com/Artiprocher/DiffSynth-Studio/assets/35051019/59fb2f7b-8de0-44
 | JoyAI-Image | [jd-opensource/JoyAI-Image-Edit](https://modelscope.cn/models/jd-opensource/JoyAI-Image-Edit) | [code](/examples/joyai_image/model_inference/JoyAI-Image-Edit.py) | [code](/examples/joyai_image/model_inference_low_vram/JoyAI-Image-Edit.py) | [code](/examples/joyai_image/model_training/full/JoyAI-Image-Edit.sh) | [code](/examples/joyai_image/model_training/validate_full/JoyAI-Image-Edit.py) | [code](/examples/joyai_image/model_training/lora/JoyAI-Image-Edit.sh) | [code](/examples/joyai_image/model_training/validate_lora/JoyAI-Image-Edit.py) |
 | ERNIE-Image | [PaddlePaddle/ERNIE-Image](https://www.modelscope.cn/models/PaddlePaddle/ERNIE-Image) | [code](/examples/ernie_image/model_inference/ERNIE-Image.py) | [code](/examples/ernie_image/model_inference_low_vram/ERNIE-Image.py) | [code](/examples/ernie_image/model_training/full/ERNIE-Image.sh) | [code](/examples/ernie_image/model_training/validate_full/ERNIE-Image.py) | [code](/examples/ernie_image/model_training/lora/ERNIE-Image.sh) | [code](/examples/ernie_image/model_training/validate_lora/ERNIE-Image.py) |
 | ERNIE-Image | [PaddlePaddle/ERNIE-Image-Turbo](https://www.modelscope.cn/models/PaddlePaddle/ERNIE-Image-Turbo) | [code](/examples/ernie_image/model_inference/ERNIE-Image-Turbo.py) | [code](/examples/ernie_image/model_inference_low_vram/ERNIE-Image-Turbo.py) | — | — | — | — |
+| LTX-2.5 | [Lightricks/LTX-2.5: DistilledPipeline-T2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2AV-DistilledPipeline.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2AV-DistilledPipeline.py) | [code](/examples/ltx2/model_training/full/LTX-2.5-T2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_full/LTX-2.5-T2AV.py) | [code](/examples/ltx2/model_training/lora/LTX-2.5-T2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_lora/LTX-2.5-T2AV.py) |
+| LTX-2.5 | [Lightricks/LTX-2.5: DistilledPipeline-I2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-I2AV-DistilledPipeline.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-I2AV-DistilledPipeline.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: TwoStagePipeline-A2V](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-A2V-TwoStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-A2V-TwoStage.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: TwoStagePipeline-Retake](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2AV-TwoStage-Retake.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2AV-TwoStage-Retake.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5-22b-IC-LoRA-Pixel-Spatial-Upscaler](https://www.modelscope.cn/models/Lightricks/LTX-2.5-22b-IC-LoRA-Pixel-Spatial-Upscaler) | [code](/examples/ltx2/model_inference/LTX-2.5-IC-LoRA-Pixel-Spatial-Upscaler.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-IC-LoRA-Pixel-Spatial-Upscaler.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: T2A](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2A.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2A.py) | - | - | - | - |
+| LTX-2.5 | [Lightricks/LTX-2.5: INT8-ConvRot](https://www.modelscope.cn/models/Lightricks/LTX-2.5) | [code](/examples/ltx2/model_inference/LTX-2.5-T2AV-INT8-ConvRot.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.5-T2AV-INT8-ConvRot.py) | - | - | - | - |
 | LTX-2 | [jd-opensource/JoyAI-Echo](https://modelscope.cn/models/jd-opensource/JoyAI-Echo) | [code](/examples/ltx2/model_inference/JoyAI-Echo-T2AV.py) | [code](/examples/ltx2/model_inference_low_vram/JoyAI-Echo-T2AV.py) | [code](/examples/ltx2/model_training/full/JoyAI-Echo-T2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_full/JoyAI-Echo-T2AV.py) | [code](/examples/ltx2/model_training/lora/JoyAI-Echo-T2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_lora/JoyAI-Echo-T2AV.py) |
 | LTX-2 | [Lightricks/LTX-2.3: OneStagePipeline-I2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.3) | [code](/examples/ltx2/model_inference/LTX-2.3-I2AV-OneStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.3-I2AV-OneStage.py) | [code](/examples/ltx2/model_training/full/LTX-2.3-I2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_full/LTX-2.3-I2AV.py) | [code](/examples/ltx2/model_training/lora/LTX-2.3-I2AV-splited.sh) | [code](/examples/ltx2/model_training/validate_lora/LTX-2.3-I2AV.py) |
 | LTX-2 | [Lightricks/LTX-2.3: TwoStagePipeline-I2AV](https://www.modelscope.cn/models/Lightricks/LTX-2.3) | [code](/examples/ltx2/model_inference/LTX-2.3-I2AV-TwoStage.py) | [code](/examples/ltx2/model_inference_low_vram/LTX-2.3-I2AV-TwoStage.py) | - | - | - | - |