README.md

🕹 Gradio Demo

We have provided a Gradio demo app for you to generate videos via a web interface. You can choose to run it locally or deploy it to Hugging Face by following the instructions given below.

🚀 Run Gradio Locally

We assume that you have already installed opensora based on the instructions given in the main README. Follow the steps below to run this app on your local machine.

1. First of all, you need to install gradio and spaces.

pip install gradio spaces

2. Afterwards, you can use the following command to launch different models. Remeber to launch the command in the project root directory instead of the gradio folder.

# run the default model v1-HQ-16x256x256
python gradio/app.py

# run the model with higher resolution
python gradio/app.py --model-type v1-HQ-16x512x512

# run with a different host and port
python gradio/app.py --port 8000 --host 0.0.0.0

# run with acceleration such as flash attention and fused norm
python gradio/app.py --enable-optimization

# run with a sharable Gradio link
python gradio/app.py --share

3. You should then be able to access this demo via the link which appears in your terminal.

📦 Deploy Gradio to Hugging Face Space

We have also tested this Gradio app on Hugging Face Spaces. You can follow the steps below.

1. Create a Space on Hugging Face, remember to choose Gradio SDK and GPU space hardware.

2. Clone the Space repository in your local machine.

3. Copy the configs folder and gradio/app.py and gradio/requirements.txt to the repository you just cloned. The file structure will look like:

- configs
    - opensora
        - inference
            - 16x256x256.py
            - 16x512x512.py
            - 64x512x512.py
        ...
    ...
- app.py
- requirements.txt
- README.md
- LICENSE
- ...

4. Push the files to your remote Hugging Face Spaces repository. The application will be built and run automatically.