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This category houses guides that are not specific to any other cagegory.
- [Dongles over IP](/docs/other/dongles-over-ip/) plug your Watchman dongles into another host on the same network
- [SVC Voice Changer](/docs/other/svc/) for AMD and NVidia GPUs, also works on CPU

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title: SVC Voice Changer
---
# SVC Voice Changer
- [so-vits-svc-fork @ GitHub](https://github.com/voicepaw/so-vits-svc-fork)
- [pre-trained models @ HuggingFace](https://huggingface.co/models?search=so-vits-svc)
so-vits-svc is one of simpler voice changers to set up on Linux. It can run on CPU as well as NVidia and AMD GPUs.
This is an exert of the original README.md of the GitHub repository, intended for people who are as bad with Python as I am.
# Setup
Disclaimer: There's probably a better way. I'm not good at Python. Or machine learning.
### Prerequisites:
Install the following packages using your distro's package manager:
- Python 3.10
- Pip for Python 3.10
- Virtualenv for Python 3.10
Please use 3.10 exactly, not newer or older.
### Create virtualenv:
In this example, we will create the virtualenv inside `~/.var/venv/`. Feel free to change the location, any folder will work.
Create virtualenv:
```bash
mkdir -p ~/.var/venv/svc/
cd ~/.var/venv/svc/
python3.10 -m venv .
```
Activate virtualenv
- On fish: `. bin/activate.fish`
- On csh: `. bin/activate.csh`
- On bash/zsh: `. bin/activate`
At this point, if you call python or pip, you will be running that command inside the virtualenv.
You can activate the virtualenv again by `cd ~/.var/venv/svc/` followed by the activate command for your shell.
To exit the virtualenv, run `deactivate`.
### Install SVC
Do these while you have the virtualenv activated.
Install required tools:
- `python -m pip install -U pip setuptools wheel`
PyTorch with CUDA support for NVIDIA GPUs:
- Please install CUDA 11.8 using your system package manager. Newer versions may not work.
- `pip install -U torch torchaudio --index-url https://download.pytorch.org/whl/cu118`
PyTorch with ROCm support for AMD GPUs:
- Please install ROCm 5.7.1 via your system package manager. Newer versions may not work.
- `pip install -U torch torchaudio --index-url https://download.pytorch.org/whl/rocm5.7`
PyTorch for CPU only (you can also choose CPU mode with the options above):
- `pip install -U torch torchaudio --index-url https://download.pytorch.org/whl/cpu`
Finally, install SVC:
- `pip install -U so-vits-svc-fork`
### Launch the GUI
You can start the graphical UI by running `svcg` inside the virtualenv.
Example start script for bash:
```bash
#!/usr/bin/env bash
. ~/.var/venv/svc/bin/activate
svcg
```
### Models
Grab a model from HuggingFace (link on top of page). Models that work with this setup are the ones tagged with `
so-vits-svc-4.0` or `so-vits-svc-4.1`.
You will need 2 files for SVC to work:
- `G_0000.pth` where 0000 is some number. Usually a higher number means better, but only if you're comparing files within the same repository.
- `config.json` tells SVC how to use the pth file.
With SVC running, plop the `G_0000.pth` into `Model Path` on the top left, and `config.json` into `Config Path`.
### Starting the Voice Changer
Default settings usually work OK. What you want to change is `Pitch`. This will be different depending on how high your own voice is compared to the model's voice. You will need different `Pitch` setting for different models.
Check `Use GPU` on the bottom center if you want to torture your GPU with your voice. It better not complain for how expensive it was.
Click `(Re)Start Voice Changer` to do just that. You also need to click this after changing any settings.
### PipeWire Setup
This is for ALVR-only right now. TODO the rest.
Use `qpwgraph` or `helvum` to:
1. Disconnect `vrserver` from `ALVR-MIC-Sink`.
2. Pipe the output of `vrserver` to the input of `Python3.10`.
3. Pipe the output of `Python3.10` to the input of `ALVR-MIC-Sink`.