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11
README.md
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@ -43,7 +43,8 @@ For users in China region, you can [click here](https://www.codewithgpu.com/i/RV
- Python 3.9, PyTorch 2.0.1, CUDA 11
- Python 3.10.13, PyTorch 2.1.2, CUDA 12.3
- Python 3.9, PyTorch 2.3.0.dev20240122, macOS 14.3 (Apple silicon)
- Python 3.9, PyTorch 2.2.2, macOS 14.4.1 (Apple silicon)
- Python 3.9, PyTorch 2.2.2, CPU devices
_Note: numba==0.56.4 requires py<3.11_
@ -51,7 +52,9 @@ _Note: numba==0.56.4 requires py<3.11_
If you are a Windows user (tested with win>=10), you can directly download the [pre-packaged distribution](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true) and double-click on _go-webui.bat_ to start GPT-SoVITS-WebUI.
Users in China region can download the file by clicking [here](https://www.icloud.com.cn/iclouddrive/061bfkcVJcBfsMfLF5R2XKdTQ#GPT-SoVITS-beta0217) and then selecting "Download a copy."
Users in China region can download [the 0217 package](https://www.icloud.com.cn/iclouddrive/061bfkcVJcBfsMfLF5R2XKdTQ#GPT-SoVITS-beta0217) or [the 0306fix2 package](https://www.icloud.com.cn/iclouddrive/09aaTLf96aa92dbLe0fPNM5CQ#GPT-SoVITS-beta0306fix2) by clicking the links and then selecting "Download a copy."
_Note: The 0306fix2 version doubles the inference speed and fixes all issues with the no reference text mode._
### Linux
@ -65,7 +68,9 @@ bash install.sh
**Note: The models trained with GPUs on Macs result in significantly lower quality compared to those trained on other devices, so we are temporarily using CPUs instead.**
First make sure you have installed FFmpeg by running `brew install ffmpeg` or `conda install ffmpeg`, then install by using the following commands:
1. Install Xcode command-line tools by running `xcode-select --install`
2. Install FFmpeg by running `brew install ffmpeg` or `conda install ffmpeg`.
3. Install the program by running the following commands:
```bash
conda create -n GPTSoVits python=3.9

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docs/cn/README.md
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@ -41,17 +41,20 @@ https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-
### 测试通过的环境
- Python 3.9、PyTorch 2.0.1 和 CUDA 11
- Python 3.10.13, PyTorch 2.1.2 和 CUDA 12.3
- Python 3.9、Pytorch 2.3.0.dev20240122 和 macOS 14.3（Apple 芯片）
- Python 3.9，PyTorch 2.0.1，CUDA 11
- Python 3.10.13，PyTorch 2.1.2，CUDA 12.3
- Python 3.9，Pytorch 2.2.2，macOS 14.4.1（Apple 芯片）
- Python 3.9，PyTorch 2.2.2，CPU 设备
_注意: numba==0.56.4 需要 python<3.11_
_注: numba==0.56.4 需要 python<3.11_
### Windows
如果你是 Windows 用户（已在 win>=10 上测试），可以直接下载[预打包文件](https://huggingface.co/lj1995/GPT-SoVITS-windows-package/resolve/main/GPT-SoVITS-beta.7z?download=true)，解压后双击 go-webui.bat 即可启动 GPT-SoVITS-WebUI。
中国地区用户可以进入[此处](https://www.icloud.com.cn/iclouddrive/061bfkcVJcBfsMfLF5R2XKdTQ#GPT-SoVITS-beta0217)并点击“下载副本”进行下载。
中国地区用户可以通过点击链接并选择“下载副本”来下载[0217版本包](https://www.icloud.com.cn/iclouddrive/061bfkcVJcBfsMfLF5R2XKdTQ#GPT-SoVITS-beta0217)或[0306fix2版本包](https://www.icloud.com.cn/iclouddrive/09aaTLf96aa92dbLe0fPNM5CQ#GPT-SoVITS-beta0306fix2)。
_注：0306fix2版本推理速度翻倍，节约生命。修复了无参考文本模式的所有问题。_
### Linux
@ -65,7 +68,9 @@ bash install.sh
**注：在 Mac 上使用 GPU 训练的模型效果显著低于其他设备训练的模型，所以我们暂时使用CPU进行训练。**
首先确保你已通过运行 `brew install ffmpeg` 或 `conda install ffmpeg` 安装 FFmpeg，然后运行以下命令安装：
1. 运行 `xcode-select --install` 安装 Xcode command-line tools。
2. 运行 `brew install ffmpeg` 或 `conda install ffmpeg` 安装 FFmpeg。
3. 完成上述步骤后，运行以下的命令来安装本项目：
```bash
conda create -n GPTSoVits python=3.9

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@ -39,7 +39,8 @@ https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-
- Python 3.9, PyTorch 2.0.1, CUDA 11
- Python 3.10.13, PyTorch 2.1.2, CUDA 12.3
- Python 3.9, PyTorch 2.3.0.dev20240122, macOS 14.3 (Apple silicon)
- Python 3.9, PyTorch 2.2.2, macOS 14.4.1 (Apple silicon)
- Python 3.9, PyTorch 2.2.2, CPUデバイス
_注記: numba==0.56.4 は py<3.11 が必要です_
@ -59,7 +60,9 @@ bash install.sh
**注：MacでGPUを使用して訓練されたモデルは、他のデバイスで訓練されたモデルと比較して著しく品質が低下するため、当面はCPUを使用して訓練します。**
まず、`brew install ffmpeg`または`conda install ffmpeg`を実行してFFmpegをインストールしたことを確認してください。次に、以下のコマンドを使用してインストールします：
1. `xcode-select --install` を実行して、Xcodeコマンドラインツールをインストールします。
2. `brew install ffmpeg` または `conda install ffmpeg` を実行して、FFmpegをインストールします。
3. 上記の手順を完了した後、以下のコマンドを実行してこのプロジェクトをインストールします。
```bash
conda create -n GPTSoVits python=3.9

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@ -37,9 +37,10 @@ https://github.com/RVC-Boss/GPT-SoVITS/assets/129054828/05bee1fa-bdd8-4d85-9350-
### 테스트 통과 환경
- Python 3.9, PyTorch 2.0.1 및 CUDA 11
- Python 3.10.13, PyTorch 2.1.2 및 CUDA 12.3
- Python 3.9, Pytorch 2.3.0.dev20240122 및 macOS 14.3 (Apple Slilicon)
- Python 3.9, PyTorch 2.0.1, CUDA 11
- Python 3.10.13, PyTorch 2.1.2, CUDA 12.3
- Python 3.9, Pytorch 2.2.2, macOS 14.4.1 (Apple Slilicon)
- Python 3.9, PyTorch 2.2.2, CPU 장치
_참고: numba==0.56.4 는 python<3.11 을 필요로 합니다._
@ -59,7 +60,9 @@ bash install.sh
**주의: Mac에서 GPU로 훈련된 모델은 다른 OS에서 훈련된 모델에 비해 품질이 낮습니다. 해당 문제를 해결하기 전까지 MacOS에선 CPU를 사용하여 훈련을 진행합니다.**
먼저 `brew install ffmpeg` 또는 `conda install ffmpeg`를 실행하여 FFmpeg가 설치되었는지 확인한 다음, 다음 명령어를 사용하여 설치하세요:
1. `xcode-select --install`을 실행하여 Xcode 커맨드라인 도구를 설치하세요.
2. `brew install ffmpeg` 또는 `conda install ffmpeg`을 실행하여 FFmpeg를 설치하세요.
3. 위의 단계를 완료한 후, 다음 명령어를 실행하여 이 프로젝트를 설치하세요.
```bash
conda create -n GPTSoVits python=3.9