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103 lines
3.2 KiB
Markdown
103 lines
3.2 KiB
Markdown
# RVC模型下载器
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[English](README.md) | 简体中文
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一个能够批量下载`yaml`清单内文件的简单工具（例如 Hugging Face 🤗 中的 RVC 模型）。
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## 快速开始
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### 准备工作
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1. 在[发布](https://github.com/RVC-Project/RVC-Models-Downloader/releases)页面下载程序。
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2. 将此程序放入RVC的根目录（或您想要下载文件的任何位置）。
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3. 您也可以将它添加到`PATH`中以便在任何地方使用此工具。如果您已经通过包管理器安装了此程序，那么它可能已经位于`PATH`。
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### 下载
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#### RVC的所有资源文件
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```bash
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rvcmd assets/all
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```
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#### RVC的最新通用整合包（仅限Windows）
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```bash
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rvcmd packs/general/latest
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```
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#### ffmpeg工具（仅限Windows）
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```bash
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rvcmd tools/ffmpeg
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```
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### 自定义下载
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#### 示例1. 下载ffmpeg工具和最新的Intel包
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1. 编写并保存以下`cust.yaml`。
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```yaml
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BaseURL: https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main
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Targets:
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- Refer: tools/ffmpeg
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- Refer: packs/intel/latest
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```
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2. 在同一文件夹中运行`rvcmd`。
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```bash
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rvcmd -c cust
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```
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#### 示例2. 下载🤗中的其他仓库
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> 以 [Stable Diffusion v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) 为例。
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1. 编写并保存以下`cust.yaml`。
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```yaml
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BaseURL: https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main
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Targets:
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- Folder: sd1.5 # the folder you want to download into
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Copy: # files to download
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- v1-5-pruned-emaonly.ckpt
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- v1-5-pruned-emaonly.safetensors
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- Folder: sd1.5/vae # the folder you want to download into
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Copy: # files to download
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- vae/diffusion_pytorch_model.bin
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```
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#### 示例3. 下载GitHub中的发布版本
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> 以 [yousa-ling-diffsinger-v1.3](https://github.com/yousa-ling-official-production/yousa-ling-diffsinger-v1/releases/tag/v1.3) 为例。
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1. 编写并保存以下`cust.yaml`。
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```yaml
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BaseURL: https://github.com/yousa-ling-official-production/yousa-ling-diffsinger-v1/releases/download/v1.3
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Targets:
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- Folder: . # the folder you want to download into
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Copy: # files to download
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- yousaV1.3.zip
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```
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2. 在同一文件夹中运行`rvcmd`。
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```bash
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rvcmd -c cust
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```
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## 完整用法
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```bash
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Usage: rvcmd [-notrs] [-dns dns.yaml] 'target/to/download'
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-c use custom yaml instruction
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-dns string
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custom dns.yaml
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-f force download even file exists
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-notrs
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use standard TLS client
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-w uint
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connection waiting seconds (default 4)
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'target/to/download'
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like packs/general/latest
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All available targets:
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assets:
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all hubert rmvpe uvr5 v1 v2
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packs:
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amd:
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latest
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v2:
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20230813 20231006
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general:
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latest
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v1:
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20230331 20230416 20230428 20230508 20230513 20230516 20230717
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v2:
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20230528 20230618
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intel:
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latest
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v2:
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20230813 20231006
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nvidia:
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latest
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v2:
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20230813 20231006
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tools:
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ffmpeg
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```
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