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examples/wanvideo/README.md
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# Wan 2.1
# Wan
[切换到中文](./README_zh.md)
Wan 2.1 is a collection of video synthesis models open-sourced by Alibaba.
Wan is a collection of video synthesis models open-sourced by Alibaba.
**DiffSynth-Studio has adopted a new inference and training framework. To use the previous version, please click [here](https://github.com/modelscope/DiffSynth-Studio/tree/3edf3583b1f08944cee837b94d9f84d669c2729c).**
@@ -247,6 +247,7 @@ The pipeline accepts the following input parameters during inference:
* `num_frames`: Number of frames, default is 81. Must be a multiple of 4 plus 1; if not, it will be rounded up, minimum is 1.
* `cfg_scale`: Classifier-free guidance scale, default is 5. Higher values increase adherence to the prompt but may cause visual artifacts.
* `cfg_merge`: Whether to merge both sides of classifier-free guidance for unified inference. Default is `False`. This parameter currently only works for basic text-to-video and image-to-video models.
* `switch_DiT_boundary`: The time point for switching between DiT models. Default value is 0.875. This parameter only takes effect for mixed models with multiple DiTs, for example, [Wan-AI/Wan2.2-I2V-A14B](https://modelscope.cn/models/Wan-AI/Wan2.2-I2V-A14B).
* `num_inference_steps`: Number of inference steps, default is 50.
* `sigma_shift`: Parameter from Rectified Flow theory, default is 5. Higher values make the model stay longer at the initial denoising stage. Increasing this may improve video quality but may also cause inconsistency between generated videos and training data due to deviation from training behavior.
* `motion_bucket_id`: Motion intensity, range [0, 100], applicable to motion control modules such as [`DiffSynth-Studio/Wan2.1-1.3b-speedcontrol-v1`](https://modelscope.cn/models/DiffSynth-Studio/Wan2.1-1.3b-speedcontrol-v1). Larger values indicate more intense motion.
@@ -282,6 +283,8 @@ The script includes the following parameters:
* Models
* `--model_paths`: Paths to load models. In JSON format.
* `--model_id_with_origin_paths`: Model ID with origin paths, e.g., Wan-AI/Wan2.1-T2V-1.3B:diffusion_pytorch_model*.safetensors. Comma-separated.
* `--max_timestep_boundary`: Maximum value of the timestep interval, ranging from 0 to 1. Default is 1. This needs to be manually set only when training mixed models with multiple DiTs, for example, [Wan-AI/Wan2.2-I2V-A14B](https://modelscope.cn/models/Wan-AI/Wan2.2-I2V-A14B).
* `--min_timestep_boundary`: Minimum value of the timestep interval, ranging from 0 to 1. Default is 1. This needs to be manually set only when training mixed models with multiple DiTs, for example, [Wan-AI/Wan2.2-I2V-A14B](https://modelscope.cn/models/Wan-AI/Wan2.2-I2V-A14B).
* Training
* `--learning_rate`: Learning rate.
* `--num_epochs`: Number of epochs.