This is a serverless application that uses Stable Diffusion XL to run a Text-to-Image task on RunPod.

See also AnimateDiff_Serverless_Runpod for Text-to-Video task.

Serverless means that you are only charged for the time you use the application, and you don't need to pay for the idle time, which is very suitable for this kind of application that is not used frequently but needs to respond quickly.

Theoretically, this application can be called by any other application. Here we provide two examples:

1. A simple Python script
2. A Telegram bot

See Usage below for more details.

Input Prompt:

A white cat, sitting next to a window, sun shining through the window.

Example Result: (40 steps, 1344x768, around 15 seconds on RTX 3090, 0.006$😱 on RunPod)

The time is measured from the moment the input prompt is sent to the moment the result image is received, including the time for all the following steps:

• Receive the request from the client
• Serverless container startup
• Model loading
• Inference
• Sending the result image back to the client.

• Python >= 3.9.7
• Docker
• Local GPU is necessary for testing but not necessary for deployment. (Recommended: RTX 3090)

If you don't have a GPU, you can modify and test the code on Google Colab and then build and deploy the application on RunPod.

# Install dependencies
pip install -r requirements.txt

# Download models
python script/download.py

# Edit (or not) config to customize your inference
edit preset_prompts.json if your want to customize your prompt

# Run inference test
python inference_util.py

# Run server.py local test
python server.py

1. First, make sure you have installed Docker and have accounts on both DockerHub and RunPod.

2. Then, decide a name for your Docker image, e.g., "your_username/sdxl:v1" and set your image name in "./scripts/build.sh".

3. Run the following commands to build and push your Docker image to DockerHub.

bash scripts/build.sh

4. Finally, deploy your application on RunPod to create Template and Endpoint.

Sorry for not providing detailed instructions here as the author is quite busy recently. You can find many detailed instructions on Google about how to deploy a Docker image on RunPod.

Feel free to contact me if you encounter any problems after searching on Google.

# Make sure to set API key and endpoint ID before running the script.
python test_client.py

• Support custom models
• Support low VRAM GPUs(8~12GB)
• More detailed instructions
• One-click deploy (If anyone is interested...)

Thanks to Stable Diffusion XL and RunPod.