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fix: no attribute 'FILE_LIKE'' & update instructions
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<div align="center">
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<h1>Retrieval-based-Voice-Conversion-WebUI</h1>
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An easy-to-use Voice Conversion framework based on VITS.<br><br>
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[](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)
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<img src="https://counter.seku.su/cmoe?name=rvc&theme=r34" /><br>
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[](https://colab.research.google.com/github/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI.ipynb)
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[](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/LICENSE)
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[](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/)
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[](https://discord.gg/HcsmBBGyVk)
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[**Changelog**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/docs/Changelog_EN.md) | [**FAQ (Frequently Asked Questions)**](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/wiki/FAQ-(Frequently-Asked-Questions))
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[**English**](../en/README.en.md) | [**中文简体**](../../README.md) | [**日本語**](../jp/README.ja.md) | [**한국어**](../kr/README.ko.md) ([**韓國語**](../kr/README.ko.han.md)) | [**Français**](../fr/README.fr.md) | [**Türkçe**](../tr/README.tr.md) | [**Português**](../pt/README.pt.md)
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</div>
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> Check out our [Demo Video](https://www.bilibili.com/video/BV1pm4y1z7Gm/) here!
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<table>
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<tr>
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<td align="center">Training and inference Webui</td>
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<td align="center">Real-time voice changing GUI</td>
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</tr>
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<tr>
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<td align="center"><img src="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/assets/129054828/092e5c12-0d49-4168-a590-0b0ef6a4f630"></td>
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<td align="center"><img src="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/assets/129054828/730b4114-8805-44a1-ab1a-04668f3c30a6"></td>
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</tr>
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<tr>
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<td align="center">go-web.bat</td>
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<td align="center">go-realtime-gui.bat</td>
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</tr>
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<tr>
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<td align="center">You can freely choose the action you want to perform.</td>
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<td align="center">We have achieved an end-to-end latency of 170ms. With the use of ASIO input and output devices, we have managed to achieve an end-to-end latency of 90ms, but it is highly dependent on hardware driver support.</td>
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</tr>
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</table>
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> The dataset for the pre-training model uses nearly 50 hours of high quality audio from the VCTK open source dataset.
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> High quality licensed song datasets will be added to the training-set often for your use, without having to worry about copyright infringement.
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> Please look forward to the pretrained base model of RVCv3, which has larger parameters, more training data, better results, unchanged inference speed, and requires less training data for training.
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## Features:
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+ Reduce tone leakage by replacing the source feature to training-set feature using top1 retrieval;
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+ Easy + fast training, even on poor graphics cards;
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+ Training with a small amounts of data (>=10min low noise speech recommended);
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+ Model fusion to change timbres (using ckpt processing tab->ckpt merge);
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+ Easy-to-use WebUI;
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+ UVR5 model to quickly separate vocals and instruments;
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+ High-pitch Voice Extraction Algorithm [InterSpeech2023-RMVPE](#Credits) to prevent a muted sound problem. Provides the best results (significantly) and is faster with lower resource consumption than Crepe_full;
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+ AMD/Intel graphics cards acceleration supported;
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+ Intel ARC graphics cards acceleration with IPEX supported.
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## Preparing the environment
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The following commands need to be executed with Python 3.8 or higher.
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(Windows/Linux)
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First install the main dependencies through pip:
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```bash
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# Install PyTorch-related core dependencies, skip if installed
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# Reference: https://pytorch.org/get-started/locally/
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pip install torch torchvision torchaudio
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#For Windows + Nvidia Ampere Architecture(RTX30xx), you need to specify the cuda version corresponding to pytorch according to the experience of https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/issues/21
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#pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
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#For Linux + AMD Cards, you need to use the following pytorch versions:
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#pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2
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```
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Then can use poetry to install the other dependencies:
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```bash
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# Install the Poetry dependency management tool, skip if installed
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# Reference: https://python-poetry.org/docs/#installation
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curl -sSL https://install.python-poetry.org | python3 -
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# Install the project dependencies
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poetry install
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```
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You can also use pip to install them:
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```bash
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for Nvidia graphics cards
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pip install -r requirements.txt
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for AMD/Intel graphics cards on Windows (DirectML)：
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pip install -r requirements-dml.txt
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for Intel ARC graphics cards on Linux / WSL using Python 3.10:
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pip install -r requirements-ipex.txt
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for AMD graphics cards on Linux (ROCm):
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pip install -r requirements-amd.txt
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```
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------
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Mac users can install dependencies via `run.sh`:
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```bash
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sh ./run.sh
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```
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## Preparation of other Pre-models
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RVC requires other pre-models to infer and train.
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```bash
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#Download all needed models from https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/
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python tools/download_models.py
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```
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Or just download them by yourself from our [Huggingface space](https://huggingface.co/lj1995/VoiceConversionWebUI/tree/main/).
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Here's a list of Pre-models and other files that RVC needs:
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```bash
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./assets/hubert/hubert_base.pt
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./assets/pretrained
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./assets/uvr5_weights
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Additional downloads are required if you want to test the v2 version of the model.
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./assets/pretrained_v2
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If you want to test the v2 version model (the v2 version model has changed the input from the 256 dimensional feature of 9-layer Hubert+final_proj to the 768 dimensional feature of 12-layer Hubert, and has added 3 period discriminators), you will need to download additional features
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./assets/pretrained_v2
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If you want to use the latest SOTA RMVPE vocal pitch extraction algorithm, you need to download the RMVPE weights and place them in the RVC root directory
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https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.pt
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For AMD/Intel graphics cards users you need download:
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https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/rmvpe.onnx
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```
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### 2. Install FFmpeg
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If you have FFmpeg and FFprobe installed on your computer, you can skip this step.
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#### For Ubuntu/Debian users
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```bash
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sudo apt install ffmpeg
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```
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#### For MacOS users
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```bash
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brew install ffmpeg
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```
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#### For Windows users
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Download these files and place them in the root folder:
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- [ffmpeg.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe)
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- [ffprobe.exe](https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe)
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## ROCm Support for AMD graphic cards (Linux only)
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To use ROCm on Linux install all required drivers as described [here](https://rocm.docs.amd.com/en/latest/deploy/linux/os-native/install.html).
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On Arch use pacman to install the driver:
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````
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pacman -S rocm-hip-sdk rocm-opencl-sdk
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````
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You might also need to set these environment variables (e.g. on a RX6700XT):
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````
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export ROCM_PATH=/opt/rocm #Set ROCM Executables Path
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export HSA_OVERRIDE_GFX_VERSION=10.3.0 #Spoof GPU Model for ROCM
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````
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And overwrite PyTorch with its ROCM version after installing dependencies.
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````
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pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2
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````
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Make sure your user is part of the `render` and `video` group:
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````
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sudo usermod -aG render $USERNAME
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sudo usermod -aG video $USERNAME
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````
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## Get started
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### start up directly
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Use the following command to start WebUI:
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```bash
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python infer-web.py
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```
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### Use the integration package
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Download and extract file `RVC-beta.7z`, then follow the steps below according to your system:
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#### For Windows users
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Double click `go-web.bat`
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#### For MacOS users
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```bash
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sh ./run.sh
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```
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### For Intel IPEX users (Linux Only)
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```bash
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source /opt/intel/oneapi/setvars.sh
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```
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## Credits
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+ [ContentVec](https://github.com/auspicious3000/contentvec/)
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+ [VITS](https://github.com/jaywalnut310/vits)
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+ [HIFIGAN](https://github.com/jik876/hifi-gan)
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+ [Gradio](https://github.com/gradio-app/gradio)
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+ [FFmpeg](https://github.com/FFmpeg/FFmpeg)
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+ [Ultimate Vocal Remover](https://github.com/Anjok07/ultimatevocalremovergui)
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+ [audio-slicer](https://github.com/openvpi/audio-slicer)
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+ [Vocal pitch extraction:RMVPE](https://github.com/Dream-High/RMVPE)
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+ The pretrained model is trained and tested by [yxlllc](https://github.com/yxlllc/RMVPE) and [RVC-Boss](https://github.com/RVC-Boss).
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## Thanks to all contributors for their efforts
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<a href="https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/graphs/contributors" target="_blank">
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<img src="https://contrib.rocks/image?repo=RVC-Project/Retrieval-based-Voice-Conversion-WebUI" />
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</a>
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@@ -23,24 +23,7 @@ Please disable system LAN proxy/global proxy and then refresh.<br>
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Training script:<br>
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You can run training in WebUI first, and the command-line versions of dataset preprocessing and training will be displayed in the message window.<br>
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Inference script:<br>
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https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/myinfer.py<br>
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e.g.<br>
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runtime\python.exe myinfer.py 0 "E:\codes\py39\RVC-beta\todo-songs\1111.wav" "E:\codes\py39\logs\mi-test\added_IVF677_Flat_nprobe_7.index" harvest "test.wav" "weights/mi-test.pth" 0.6 cuda:0 True<br>
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f0up_key=sys.argv[1]<br>
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input_path=sys.argv[2]<br>
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index_path=sys.argv[3]<br>
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f0method=sys.argv[4]#harvest or pm<br>
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opt_path=sys.argv[5]<br>
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model_path=sys.argv[6]<br>
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index_rate=float(sys.argv[7])<br>
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device=sys.argv[8]<br>
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is_half=bool(sys.argv[9])<br>
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Inference script: tool/cmd/infer_cli.py
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## Q7:Cuda error/Cuda out of memory.
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There is a small chance that there is a problem with the CUDA configuration or the device is not supported; more likely, there is not enough memory (out of memory).<br>
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