Open-Sora/gradio/README.md
2024-04-06 23:34:55 +08:00

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# 🕹 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](../README.md). Follow the steps below to run this app on your local machine.
1. First of all, you need to install `gradio` and `spaces`.
```bash
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.
```bash
# 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:
```text
- 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.