Update README.md

README.md

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 license: apache-2.0
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-<h2 align="center">lyraDiff: An Out-of-box Acceleration Engine for Diffusion and DiT Models</h2>
-<div align="center">   
-Sa Xiao<sup>*</sup>, Yibo Lu<sup>*</sup>,  Kangjian Wu<sup>*</sup>, Bin Wu<sup>†</sup>, Haoxiong Su, Mian Peng, Qiwen Mao, Wenjiang Zhou</br>(*co-first author), (†Corresponding Author, benbinwu@tencent.com)</br>
-Lyra Lab, Tencent Music Entertainment</br>     
-<p>[<a href="https://github.com/TMElyralab/lyraDiff">github</a>] </p>
-</div>    
+<div align="center">
 
-## Introduction
+<h1> lyraDiff: An Out-of-the-box Acceleration Engine for Diffusion and DiT Models</h1>
 
-🌈`lyraDiff` is currently the **Fastest Diffusion Acceleration Engine** that **doesn't need recompilation with dynamic input shapes**.
+</div> 
 
-The core features include:
-- 🚀 **State-of-the-art Inference Speed**: `lyraDiff` utilizes multiple techniques to achieve up to 2x speedup of the model inference, including **Quantization**, **Fused GEMM Kernels**, **Flash Attention**, and **NHWC & Fused GroupNorm**.
-- 🔥 **Memory Efficiency**: `lyraDiff` utilizes buffer-based DRAM reuse strategy and multiple types of quantizations (FP8/INT8/INT4) to save **10-40%** of DRAM usage.
-- 🔥 **Extensive Model Support**: `lyraDiff` supports a wide range of Generative/SR models such as **SD1.5, SDXL, FLUX, S3Diff, SUPIR, etc.**, and those most commonly used plugins such as **LoRA, ControlNet and Ip-Adapter**.
-- 🔥 **Zero Compilation Deployment**: Unlike **TensorRT** or **AITemplate**, which takes minutes to compile, `lyraDiff` eliminates runtime recompilation overhead even with model inputs of dynamic shapes.
-- 🔥 **Image Gen Consistency**: The outputs of `lyraDiff` are aligned with the ones of [HF diffusers](https://github.com/huggingface/diffusers) at the pixel level, even under LoRA switch in quantization mode.
-- 🚀 **Fast Plugin Hot-swap**: `lyraDiff` provides **Super Fast Model Hot-swap for ControlNet and LoRA** which can hugely benefit a real-time image gen service.
 
+`lyraDiff` introduces a **recompilation-free** inference engine for Diffusion and DiT models, achieving **state-of-the-art speed**, **extensive model support**, and **pixel-level image consistency**.
 
-![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6461b412846a6c8c8305319d/IAcfgrmYOcRS9vcNqvkzH.jpeg)
-
-`lyraDiff-IP-Adapters` is converted from the standard [IP-Adapter](https://huggingface.co/h94/IP-Adapter) weights using this [script](https://github.com/TMElyralab/lyraDiff/blob/main/lyradiff/convert_model_scripts/convert_ipadapter.py) to be compatiable with [lyraDiff](https://github.com/TMElyralab/lyraDiff), and contains both SD1.5 and SDXL version of converted IP-Adapter
+## Highlights
+- **State-of-the-art Inference Speed**: `lyraDiff` utilizes multiple techniques to achieve up to **6.1x** speedup of the model inference, including **Quantization**, **Fused GEMM Kernels**, **Flash Attention**, and **NHWC & Fused GroupNorm**.
+- **Memory Efficiency**: `lyraDiff` utilizes buffer-based DRAM reuse strategy and multiple types of quantizations (FP8/INT8/INT4) to save **10-40%** of DRAM usage.
+- **Extensive Model Support**: `lyraDiff` supports a wide range of top Generative/SR models such as **SD1.5, SDXL, FLUX, S3Diff, etc.**, and those most commonly used plugins such as **LoRA, ControlNet and Ip-Adapter**.
+- **Zero Compilation Deployment**: Unlike **TensorRT** or **AITemplate**, which takes minutes to compile, `lyraDiff` eliminates runtime recompilation overhead even with model inputs of dynamic shapes.
+- **Image Gen Consistency**: The outputs of `lyraDiff` are aligned with the ones of [HF diffusers](https://github.com/huggingface/diffusers) at the pixel level, even under LoRA switch in quantization mode.
+- **Fast Plugin Hot-swap**: `lyraDiff` provides **Super Fast Model Hot-swap for ControlNet and LoRA** which can hugely benefit a real-time image gen service.
 
 ## Usage
 
-<!-- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6461b412846a6c8c8305319d/8U6yNHTPLaOC3gIWJZWGL.png)
- -->
+`lyraDiff-IP-Adapters` is converted from the standard [IP-Adapter](https://huggingface.co/h94/IP-Adapter) weights using this [script](https://github.com/TMElyralab/lyraDiff/blob/main/lyradiff/convert_model_scripts/convert_ipadapter.py) to be compatiable with [lyraDiff](https://github.com/TMElyralab/lyraDiff), and contains both SD1.5 and SDXL version of converted IP-Adapter
+
 We provide a reference implementation of lyraDiff version of SD1.5/SDXL, as well as sampling code, in a dedicated [github repository](https://github.com/TMElyralab/lyraDiff).
 
 ### Example