Update README.md

README.md

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-title: LeVo Song Generation
+title: Song Generation
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-# SongGeration:
+<p align="center">
+    <a href="https://levo-demo.github.io/">Demo</a> &nbsp;|&nbsp; <a href="https://arxiv.org/abs/2506.07520">Paper</a>  &nbsp;|&nbsp; <a href="https://github.com/tencent-ailab/songgeneration">Code</a>
+</p>
 
-This repository is the official code repository for LeVo: High-Quality Song Generation with Multi-Preference Alignment. You can find our paper on [here](https://arxiv.org/). The demo page is available [here](https://levo-demo.github.io/).
+This repository is the official weight repository for LeVo: High-Quality Song Generation with Multi-Preference Alignment. In this repository, we provide the SongGeneration model, inference scripts, and the checkpoint that has been trained on the Million Song Dataset.
 
-In this repository, we provide the SongGeration model, inference scripts, and the checkpoint that has been trained on the Million Song Dataset. Specifically, we have released the model and inference code corresponding to the SFT + auto-DPO version.
+## Overview
 
-## Installation
+We develop the SongGeneration model. It is an LM-based framework consisting of **LeLM** and a **music codec**. LeLM is capable of parallelly modeling two types of tokens: mixed tokens, which represent the combined audio of vocals and accompaniment to achieve vocal-instrument harmony, and dual-track tokens, which separately encode vocals and accompaniment for high-quality song generation. The music codec reconstructs the dual-track tokens into highfidelity music audio. SongGeneration significantly improves over the open-source music generation models and performs competitively with current state-of-the-art industry systems. For more details, please refer to our [paper](https://arxiv.org/abs/2506.07520).
 
-## Start from scatch
-You can install the necessary dependencies using the `requirements.txt` file with Python 3.8.12:
-
-```bash
-pip install -r requirements.txt
-```
-
-then install flash attention from wget
-
-```bash
-wget https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu12torch2.2cxx11abiFALSE-cp310-cp310-linux_x86_64.whl -P /home/
-pip install /home/flash_attn-2.7.4.post1+cu12torch2.2cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
-```
-
-## Start with docker
-```bash
-docker pull juhayna/song-generation-levo:v0.1
-docker run -it --gpus all --network=host juhayna/song-generation-levo:v0.1 /bin/bash
-```
-
-## Inference
-
-Please note that all the two folder below must be downloaded completely for the model to load correctly, which is sourced from [here](https://huggingface.co/waytan22/SongGeneration)
-
-- Save `ckpt` to the root directory
-- Save `third_party` to the root directory
-
-Then run inference, use the following command:
-
-```bash
-sh generate.sh sample/lyric.jsonl sample/generate
-```
-- Input keys in the `sample/lyric.jsonl`
-  - `idx`: name of the generate song file
-  - `descriptions`: text description, can be None or specified gender, timbre, genre, mood, instrument and BPM
-  - `prompt_audio_path`: reference audio path, can be None or 10s song audio path
-  - `gt_lyric`: lyrics, it needs to follow the format of '\[Structure\] Text', supported structures can be found in `conf/vocab.yaml`
-
-- Outputs of the loader `sample/generate`:
-  - `audio`: generated audio files
-  - `jsonl`: output jsonls
-  - `token`: Token corresponding to the generated audio files
+<img src="https://github.com/tencent-ailab/songgeneration/blob/main/img/over.jpg?raw=true" alt="img" style="zoom:100%;" /> 
 
 ## Note