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sdxl-turbo-tensorrt

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metadata 
pipeline_tag: text-to-image
inference: false
library_name: tensorrt
license: other
license_name: sai-nc-community
license_link: https://huggingface.co/stabilityai/sdxl-turbo/blob/main/LICENSE.TXT
tags:
  - tensorrt
  - sdxl-turbo
  - text-to-image
  - onnx

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

Accelerator CLIP Unet VAE Total
A100 1.03 ms 79.31 ms 53.69.34 ms 138.57 ms
H100 0.78 ms 48.87 ms 30.35 ms 83.8 ms

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
  1. 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 ..
  1. 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
  1. 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