---
title: Wan2.1-1.3b-lora-speedcontrol-v1
canonical_url: "https://www.modelscope.cn/models/DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1"
md_url: "https://www.modelscope.cn/models/DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1.md"
repository: DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1
chinese_name: "速度控制-通义万相2.1-1.3B-LoRA-v1"
last_updated: 2025-03-07
license: "Apache License 2.0"
pipeline_tag: text-to-video-synthesis
tasks:
  - text-to-video-synthesis
base_model:
  - "MusePublic/wan2.1-1.3b@v1"
base_model_relation: adapter
parameters: 21.9M
tensor_type:
  - F32
library_name:
  - pytorch
  - lora
  - safetensors
frameworks:
  - Pytorch
downloads: 435
stars: 9
tags:
  - LoRA
  - "text2video generation"
---

# Wan2.1-1.3b-lora-speedcontrol-v1

> Wan2.1-1.3b-lora-speedcontrol-v1 - DiffSynth-Studio 在 ModelScope 开源的模型。通义万相2.1-1.3B-LoRA-速度控制-v1

DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1 是 ModelScope 魔搭社区上的 21.9M 参数text-to-video-synthesis模型，采用 Apache License 2.0 许可，基于 MusePublic/wan2.1-1.3b@v1 构建。

- **Repository**: DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1
- **License**: Apache License 2.0
- **Tasks**: text-to-video-synthesis
- **Parameters**: 21.9M
- **Base model**: MusePublic/wan2.1-1.3b@v1
- **Tags**: LoRA, text2video generation
- **Downloads**: 435
- **Stars**: 9
- **Last updated**: 2025-03-07

Source: https://www.modelscope.cn/models/DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1

---

# 通义万相2.1-1.3B-LoRA-速度控制-v1

## 模型介绍

本 LoRA 模型是基于模型[通义万相2.1-1.3B](https://www.modelscope.cn/models/Wan-AI/Wan2.1-T2V-1.3B)和框架 [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) 训练的LoRA。本模型可以通过调整 LoRA alpha 参数控制视频的速度。

* **LoRA alpha > 0**: 使用触发词 low speed，速度变慢，画质增强
* **LoRA alpha < 0**: 使用触发词 high speed，速度变快，画质降低

**目前本模型的效果还不够稳定，我们还在继续优化中。**

## 模型效果

提示词：纪实摄影风格画面，一只活泼的白色小狗在绿茵茵的草地上迅速奔跑。小狗毛色雪白，两只耳朵立起，神情专注而欢快。阳光洒在它身上，使得毛发看上去格外柔软而闪亮。背景是一片开阔的草地，偶尔点缀着几朵野花，远处隐约可见蓝天和几片白云。透视感鲜明，捕捉小狗奔跑时的动感和四周草地的生机。中景侧面移动视角。

负面提示词：色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走

LoRA alpha = 0.7

<div align="center"><video width="80%" controls><source src="assets/0.7.mp4" type="video/mp4">Your browser does not support the video tag.</video></div>

LoRA alpha = 0

<div align="center"><video width="80%" controls><source src="assets/0.mp4" type="video/mp4">Your browser does not support the video tag.</video></div>

LoRA alpha = -0.5

<div align="center"><video width="80%" controls><source src="assets/-0.5.mp4" type="video/mp4">Your browser does not support the video tag.</video></div>

## 使用说明

本模型基于框架 [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) 训练，请先安装

```
pip install diffsynth
```


```python
import torch
from diffsynth import ModelManager, WanVideoPipeline, save_video
from modelscope import snapshot_download


snapshot_download(
    model_id="DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1",
    local_dir="models/DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1",
    allow_file_pattern="*.safetensors"
)
model_manager = ModelManager(device="cpu")
model_manager.load_models(
    [
        "models/Wan-AI/Wan2.1-T2V-1.3B/diffusion_pytorch_model.safetensors",
        "models/Wan-AI/Wan2.1-T2V-1.3B/models_t5_umt5-xxl-enc-bf16.pth",
        "models/Wan-AI/Wan2.1-T2V-1.3B/Wan2.1_VAE.pth",
    ],
    torch_dtype=torch.bfloat16,
)
model_manager.load_lora("models/DiffSynth-Studio/Wan2.1-1.3b-lora-speedcontrol-v1/model.safetensors", lora_alpha=0.7)
pipe = WanVideoPipeline.from_model_manager(model_manager, torch_dtype=torch.bfloat16, device="cuda")
pipe.enable_vram_management(num_persistent_param_in_dit=None)

video = pipe(
    prompt="low speed, 纪实摄影风格画面，一只活泼的白色小狗在绿茵茵的草地上迅速奔跑。小狗毛色雪白，两只耳朵立起，神情专注而欢快。阳光洒在它身上，使得毛发看上去格外柔软而闪亮。背景是一片开阔的草地，偶尔点缀着几朵野花，远处隐约可见蓝天和几片白云。透视感鲜明，捕捉小狗奔跑时的动感和四周草地的生机。中景侧面移动视角。",
    negative_prompt="色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走",
    num_inference_steps=50,
    seed=0, tiled=True,
)
save_video(video, "video.mp4", fps=15, quality=5)
```