update readme

Author: helloyongyang

README.md

@@ -35,9 +35,12 @@ Besides the contributions from the LightX2V team, we have received contributions
 
 - [triple-Mu](https://github.com/triple-Mu)
 - [vivienfanghuagood](https://github.com/vivienfanghuagood)
+- [yeahdongcn](https://github.com/yeahdongcn)
 
 ## :fire: Latest News
 
+- **December 27, 2025:** 🚀 Supported deployment on MThreads MUSA.
+
 - **December 25, 2025:** 🚀 Supported deployment on AMD ROCm and Ascend 910B.
 
 - **December 23, 2025:** 🚀 We support the [Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511) image editing model since Day 0. On a single H100 GPU, LightX2V delivers approximately 1.4× speedup. We support for CFG parallelism, Ulysses parallelism, and efficient offloading technologies. Our [HuggingFace](https://huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning) has been updated with CFG / step-distilled LoRA and FP8 weights. Usage examples can be found in the [Python scripts](https://github.com/ModelTC/LightX2V/tree/main/examples/qwen_image). Combined with LightX2V, 4-step CFG / step distillation, and the FP8 model, the maximum acceleration can reach up to approximately 42×. Feel free to try [LightX2V Online Service](https://x2v.light-ai.top/login) with *Image to Image* and *Qwen-Image-Edit-2511* model.

README_zh.md

@@ -35,9 +35,12 @@ pre-commit run --all-files
 
 - [triple-Mu](https://github.com/triple-Mu)
 - [vivienfanghuagood](https://github.com/vivienfanghuagood)
+- [yeahdongcn](https://github.com/yeahdongcn)
 
 ## :fire: 最新动态
 
+- **2025年12月27日:** 🚀 支持摩尔线程 MUSA 的部署。
+
 - **2025年12月25日:** 🚀 支持 AMD ROCm 和 Ascend 910B 的部署。
 
 - **2025年12月23日:** 🚀 我们Day0支持了[Qwen/Qwen-Image-Edit-2511](https://huggingface.co/Qwen/Qwen-Image-Edit-2511)的图像编辑模型，H100单卡，LightX2V可带来约1.4倍的速度提升，支持CFG并行/Ulysses并行，高效Offload等技术。我们的[HuggingFace](https://huggingface.co/lightx2v/Qwen-Image-Edit-2511-Lightning)已经更新了CFG/步数蒸馏lora和FP8权重。使用方式可以参考[Python脚本](https://github.com/ModelTC/LightX2V/tree/main/examples/qwen_image)。结合LightX2V，4步CFG/步数蒸馏，FP8模型，最高可以加速约42倍。可以在[LightX2V 在线服务](https://x2v.light-ai.top/login)的图生图的Qwen-Image-Edit-2511进行体验。

lightx2v_platform/README_zh.md

@@ -11,6 +11,7 @@
 - 海光DCU
 - 华为Ascend 910B
 - AMD ROCm
+- 摩尔线程 MUSA
 
 相关的docker环境可以参考：https://github.com/ModelTC/LightX2V/tree/main/dockerfiles/platforms
 

lightx2v_platform/base/__init__.py

@@ -1,6 +1,6 @@
+from lightx2v_platform.base.base import check_ai_device, init_ai_device  # noqa
 from lightx2v_platform.base.amd_rocm import AmdRocmDevice
 from lightx2v_platform.base.ascend_npu import NpuDevice
-from lightx2v_platform.base.base import check_ai_device, init_ai_device  # noqa
 from lightx2v_platform.base.cambricon_mlu import MluDevice
 from lightx2v_platform.base.hygon_dcu import HygonDcuDevice
 from lightx2v_platform.base.metax import MetaxDevice

lightx2v_platform/base/mthreads_musa.py

@@ -4,7 +4,7 @@
 
 @PLATFORM_DEVICE_REGISTER("musa")
 class MusaDevice(CudaDevice):
-    name = "cuda"
+    name = "musa"
 
     @staticmethod
     def is_available() -> bool: