ardha27

AI-Song-Cover-RVC

All-in-one RVC song cover toolkit for Google Colab: pull audio from YouTube, separate vocals, train a model, and run inference.

ApplicationsContent creationJupyter Notebook

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创建于 2023-05-06 · 更新于 2026-10-15 · 今日第 11089 名

主要开发者

ardha27

MinatoIsuki

mocci24

ardha27/AI-Song-Cover-RVC 排名第 11,089，有 1,221 个星标。

同类别比较

ardha27/AI-Song-Cover-RVC 排名第 11,089，此处有 8 个同类条目；engcang/SLAM-application 排名第 11,091。

同类别比较
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benrugg/AI-Render	11,074	语言: Python 星标数: 1,225 分叉数: 92 简介: Stable Diffusion in Blender
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关键参数与规格

关键参数与规格
参数	值
语言	Jupyter Notebook
类别	Applications
子类别	Content creation
关键词	Audio production, Voice cloning
星标数	1,221
分叉数	162
贡献者	3
创建日期	2023-05-06
更新日期	2026-10-15
1 天星标数	0
7 天星标数	2
排名	11,089
上次排名	5,887
排名变化	-5,202
7 天星标排名	8,159
上次 7 天星标排名	8,220
7 天星标排名变化	61
总星标排名	9,567
上次总星标排名	9,558
总星标排名变化	-9
国家	Indonesia

README 摘录

AI-Song-Cover-RVC Everything you need for RVC voice covers in one place, run on Google Colab or Kaggle: download YouTube audio as WAV, separate vocals, split audio, train models, and run inference. Make Sure To Leave A Star If This Repo Was Helpful :) Tutorial (Indonesian) RVC Colab Free Tutorial (Training & Inference) AICoverGen Colab Free Tutorial (Inference) Download YouTube WAV and Splitting Audio Training Without UI/Gradio, Prevent Banning (Colab Free) Read this tutorial Download Training Assets Run Training

(Run the Asset Download Above First) AICoverGen Mod by Me & Hina (Colab Free) AICoverGen by SociallyIneptWeeb (Without UI, Colab Pro Only) Training V2 with YouTube Audio Download and Splitting, Combined by MinatoIsuki (With UI, Colab Pro Only)

常见问题

记录了多少星标和分叉？

ardha27/AI-Song-Cover-RVC 有 1,221 个星标和 162 个分叉。

仓库排名是多少？

ardha27/AI-Song-Cover-RVC 排名第 11,089。

记录的语言和类别是什么？

ardha27/AI-Song-Cover-RVC 有 1,221 个星标，语言为 Jupyter Notebook，类别为 Applications。

哪个仓库排名最接近？

ardha27/AI-Song-Cover-RVC 与 engcang/SLAM-application 比较，后者排名第 11,091，有 1,221 个星标。

README

AI-Song-Cover-RVC

Everything you need for RVC voice covers in one place, run on Google Colab or Kaggle: download YouTube audio as WAV, separate vocals, split audio, train models, and run inference.