Update README.md

README.md

@@ -19,7 +19,7 @@ inference:
 
 ## Overview
 
-Wan2.1-T2V-14B-StepDistill-CfgDistill is an advanced text-to-video generation model built upon the Wan2.1-T2V-14B foundation. This approach allows the model to generate videos with significantly fewer inference steps (4 or 8 steps) and without classifier-free guidance, substantially reducing video generation time while maintaining high quality outputs.
+Wan2.1-T2V-14B-StepDistill-CfgDistill is an advanced text-to-video generation model built upon the Wan2.1-T2V-14B foundation. This approach allows the model to generate videos with significantly fewer inference steps (4 steps) and without classifier-free guidance, substantially reducing video generation time while maintaining high quality outputs.
 
 ## Video Demos
 
@@ -34,7 +34,7 @@ Our training code is modified based on the [Self-Forcing](https://github.com/gua
 Our inference framework utilizes [lightx2v](https://github.com/ModelTC/lightx2v), a highly efficient inference engine that supports multiple models. This framework significantly accelerates the video generation process while maintaining high quality output.
 
 ```bash
-bash scripts/run_wan_t2v_distill.sh
+bash scripts/wan/run_wan_t2v_distill_4step_cfg.sh
 ```
 
 ## License Agreement