---
title: naturalspeech2_libritts
canonical_url: "https://www.modelscope.cn/models/AI-ModelScope/naturalspeech2_libritts"
md_url: "https://www.modelscope.cn/models/AI-ModelScope/naturalspeech2_libritts.md"
repository: AI-ModelScope/naturalspeech2_libritts
last_updated: 2023-12-20
license: mit
downloads: 25
stars: 0
---

# naturalspeech2_libritts

> naturalspeech2_libritts - AI-ModelScope 在 ModelScope 开源的模型。Pretrained Model of Amphion NaturalSpeech2

AI-ModelScope/naturalspeech2_libritts 是 ModelScope 魔搭社区上的机器学习模型，采用 mit 许可。

- **Repository**: AI-ModelScope/naturalspeech2_libritts
- **License**: mit
- **Downloads**: 25
- **Stars**: 0
- **Last updated**: 2023-12-20

Source: https://www.modelscope.cn/models/AI-ModelScope/naturalspeech2_libritts

---

# Pretrained Model of Amphion NaturalSpeech2

We provide the pre-trained checkpoint of [NaturalSpeech2](https://github.com/open-mmlab/Amphion/tree/main/egs/tts/NaturalSpeech2) trained on [LibriTTS](https://github.com/open-mmlab/Amphion/tree/main/egs/datasets#libritts), which is is a multi-speaker English corpus of approximately 585 hours of read English speech at 24kHz.

Note that the current model is only trained on libritts, and the amount of training data is much less than the 5.5w hours of the original paper. We will soon introduce models trained on large-scale data. Please stay tuned.

## Quick Start

To utilize the pretrained models, just run the following commands:

### Step1: Download the checkpoint
```bash
git lfs install
git clone https://huggingface.co/amphion/naturalspeech2_libritts
```

### Step2: Clone the Amphion's Source Code of GitHub
```bash
git clone https://github.com/open-mmlab/Amphion.git
```

### Step3: Specify the checkpoint's path
Use the soft link to specify the downloaded checkpoint in the first step:

```bash
cd Amphion
mkdir -p ckpts
ln -s  ../../../naturalspeech2_libritts  ckpts/tts/
```

### Step4: Inference

You can follow the inference part of [this recipe](https://github.com/open-mmlab/Amphion/tree/main/egs/tts/NaturalSpeech2/README.md) to generate speech from text.

We also provided an online [demo](https://huggingface.co/spaces/amphion/NaturalSpeech2), feel free to try it!