SDXL-Turbo Tensorrt

Introduction

This repository hosts the TensorRT version of Stable Diffusion XL Turbo created in collaboration with NVIDIA. The optimized versions give substantial improvements in speed and efficiency.

SDXL-Turbo is a fast generative text-to-image model that can synthesize photorealistic images from a text prompt in a single network evaluation. A real-time demo is available here: http://clipdrop.co/stable-diffusion-turbo

Model Details

Model Description

SDXL-Turbo is a distilled version of SDXL 1.0, trained for real-time synthesis.

• Developed by: Stability AI
• Model type: Generative text-to-image model
• Model Description: This is a conversion of the SDXL Turbo

Performance

Timings for 4 steps at 512x512

Usage Example

1. Following the setup instructions on launching a TensorRT NGC container.

git clone https://github.com/rajeevsrao/TensorRT.git
cd TensorRT
git checkout release/9.2
docker run --rm -it --gpus all -v $PWD:/workspace nvcr.io/nvidia/pytorch:23.11-py3 /bin/bash

2. Download the SDXL-Turbo TensorRT files from this repo

git lfs install 
git clone https://huggingface.co/stabilityai/sdxl-turbo-tensorrt
cd sdxl-turbo-tensorrt
git lfs pull
cd ..

3. Install libraries and requirements

cd demo/Diffusion
python3 -m pip install --upgrade pip
pip3 install -r requirements.txt
python3 -m pip install --pre --upgrade --extra-index-url https://pypi.nvidia.com tensorrt

4. Perform TensorRT optimized inference:

• SDXL Turbo

  Works best for 512x512 images and EulerA scheduler. The first invocation produces plan files in --engine-dir specific to the accelerator being run on and are reused for later invocations.

  python3 demo_txt2img_xl.py \
    ""Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"" \
    --version=xl-turbo \
    --onnx-dir /workspace/sdxl-turbo-tensorrt/ \
    --engine-dir /workspace/sdxl-turbo-tensorrt/engine \
    --denoising-steps 4 \
    --guidance-scale 0.0 \
    --seed 42 \
    --width 512 \
    --height 512