How to Run Stable Video Diffusion Locally

Official website

My system environment

  • Memory 64G
  • 3090 GPU, 24G video memory

Step one: Download

  1. clone official repository
git clone

cd generative-models
  1. Download model

There are 4 models, any one can be used, storage directory: generative-models/checkpoints

Step two: Python environment configuration

conda create --name svd python=3.10 -y

source activate svd

pip3 install -r requirements/pt2.txt

pip3 install .

Step three: Run

cd generative-models

streamlit run scripts/demo/  --server.address  --server.port 7862

When starting, two more models will be downloaded, you can manually download and put in the following directory:



Download address:

Continue to run, if report error

from scripts.demo.streamlit_helpers import *

ModuleNotFoundError: No module named 'scripts'

add environment variable

RUN echo 'export PYTHONPATH=/generative-models:$PYTHONPATH' >>  /root/.bashrc

source /root/.bashrc

Start again successfully, you can access stable video diffusion locally:

Step four: Use

  • Access local stable video diffusion
  • Start operation, select model version, then check, speed depends on machine configuration, takes 2-3 minutes on our computer.
  • Select image upload
  • Change the number of frames in the red box to 2, too big, memory error prone, other parameters remain unchanged. Click 'Sample', and then look backstage
  • Processing is complete, take a look at the video, the video is saved in generative-models/outputs/demo/vid/svd_image_decoder/samples, you can see a 2 second video has been generated