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lightx2v
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Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v

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@@ -37,13 +37,13 @@ Our training code is modified based on the [Self-Forcing](https://github.com/gua
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  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.
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  ```bash
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- bash scripts/distill/run_wan_t2v_distill_4step_cfg.sh
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  ```
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  or using the lora version:
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  ```bash
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- bash scripts/distill/run_wan_t2v_distill_4step_cfg_lora.sh
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  ```
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  We recommend using the **LCM scheduler** with the following settings:
 
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  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.
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  ```bash
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+ bash scripts/wan/run_wan_t2v_distill_4step_cfg.sh
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  ```
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  or using the lora version:
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  ```bash
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+ bash scripts/wan/run_wan_t2v_distill_4step_cfg_lora.sh
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  ```
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  We recommend using the **LCM scheduler** with the following settings: