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64 lines
1.9 KiB
Markdown
64 lines
1.9 KiB
Markdown
# 🕹 Gradio Demo
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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.
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## 🚀 Run Gradio Locally
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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.
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1. First of all, you need to install `gradio` and `spaces`.
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```bash
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pip install gradio spaces
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```
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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.
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```bash
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# run the default model v1-HQ-16x256x256
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python gradio/app.py
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# run the model with higher resolution
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python gradio/app.py --model-type v1-HQ-16x512x512
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# run with a different host and port
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python gradio/app.py --port 8000 --host 0.0.0.0
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# run with acceleration such as flash attention and fused norm
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python gradio/app.py --enable-optimization
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# run with a sharable Gradio link
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python gradio/app.py --share
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```
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3. You should then be able to access this demo via the link which appears in your terminal.
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## 📦 Deploy Gradio to Hugging Face Space
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We have also tested this Gradio app on Hugging Face Spaces. You can follow the steps below.
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1. Create a Space on Hugging Face, remember to choose `Gradio SDK` and GPU space hardware.
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2. Clone the Space repository in your local machine.
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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:
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```text
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- configs
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- opensora
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- inference
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- 16x256x256.py
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- 16x512x512.py
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- 64x512x512.py
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...
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...
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- app.py
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- requirements.txt
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- README.md
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- LICENSE
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- ...
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```
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4. Push the files to your remote Hugging Face Spaces repository. The application will be built and run automatically.
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