Windows setup meant for use with SkyrimNet either locally (or local secondary PC) install of Zonos

• In SkyriNet UI highly suggest using "Zyphra/Zonos-v0.1-transformer" and disabling Random Seed
• should support Blackwell cards but not Ampere or below
• cache files in cache folder
• output files saved in output_tmp folder under process timestamp folders

Assumes that Python 3.12 is already installed.

To install other needed files:

1_Install.bat or 1_Install.ps1

To run:

2_Start_Zonos.bat or 2_Start_Zonos.ps1

This should start in a high priority process window.

Requirements that should be handled by 1_Install:

• eSpeak

• Windows Visual Studio x64 C++ Build Tools

• Python 3.12 Virtual Environment

  • py -3.12 -m venv .venv
  • .venv\Scripts\activate
  • pip install --upgrade pip
  • pip install -r requirements.txt

Startup handled by 2_Start_Zonos:

• Either run from an x64 VS Tools Command Prompt or PowerShell or activate using the vcvars64.bat script:
  • 'C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Auxiliary\Build\vcvars64.bat'
• Use virtual environment:
  • .venv\Scripts\activate or .venv\Scripts\Activate.ps1 (for Powershell)
• Run Zonos:
  • python SkyrimNet-Zonos.py

Zonos-v0.1 is a leading open-weight text-to-speech model trained on more than 200k hours of varied multilingual speech, delivering expressiveness and quality on par with—or even surpassing—top TTS providers.

Our model enables highly natural speech generation from text prompts when given a speaker embedding or audio prefix, and can accurately perform speech cloning when given a reference clip spanning just a few seconds. The conditioning setup also allows for fine control over speaking rate, pitch variation, audio quality, and emotions such as happiness, fear, sadness, and anger. The model outputs speech natively at 44kHz.

Zonos follows a straightforward architecture: text normalization and phonemization via eSpeak, followed by DAC token prediction through a transformer or hybrid backbone. An overview of the architecture can be seen below.

import torch
import torchaudio
from zonos.model import Zonos
from zonos.conditioning import make_cond_dict
from zonos.utils import DEFAULT_DEVICE as device

# model = Zonos.from_pretrained("Zyphra/Zonos-v0.1-hybrid", device=device)
model = Zonos.from_pretrained("Zyphra/Zonos-v0.1-transformer", device=device)

wav, sampling_rate = torchaudio.load("assets/exampleaudio.mp3")
speaker = model.make_speaker_embedding(wav, sampling_rate)

cond_dict = make_cond_dict(text="Hello, world!", speaker=speaker, language="en-us")
conditioning = model.prepare_conditioning(cond_dict)

codes = model.generate(conditioning)

wavs = model.autoencoder.decode(codes).cpu()
torchaudio.save("sample.wav", wavs[0], model.autoencoder.sampling_rate)

uv run gradio_interface.py
# python gradio_interface.py

This should produce a sample.wav file in your project root directory.

For repeated sampling we highly recommend using the gradio interface instead, as the minimal example needs to load the model every time it is run.

• Zero-shot TTS with voice cloning: Input desired text and a 10-30s speaker sample to generate high quality TTS output
• Audio prefix inputs: Add text plus an audio prefix for even richer speaker matching. Audio prefixes can be used to elicit behaviours such as whispering which can otherwise be challenging to replicate when cloning from speaker embeddings
• Multilingual support: Zonos-v0.1 supports English, Japanese, Chinese, French, and German
• Audio quality and emotion control: Zonos offers fine-grained control of many aspects of the generated audio. These include speaking rate, pitch, maximum frequency, audio quality, and various emotions such as happiness, anger, sadness, and fear.
• Fast: our model runs with a real-time factor of ~2x on an RTX 4090 (i.e. generates 2 seconds of audio per 1 second of compute time)
• Gradio WebUI: Zonos comes packaged with an easy to use gradio interface to generate speech
• Simple installation and deployment: Zonos can be installed and deployed simply using the docker file packaged with our repository.

• Operating System: Linux (preferably Ubuntu 22.04/24.04), macOS
• GPU: 6GB+ VRAM, Hybrid additionally requires a 3000-series or newer Nvidia GPU

Note: Zonos can also run on CPU provided there is enough free RAM. However, this will be a lot slower than running on a dedicated GPU, and likely won't be sufficient for interactive use.

For experimental windows support check out this fork.

See also Docker Installation

Zonos depends on the eSpeak library phonemization. You can install it on Ubuntu with the following command:

apt install -y espeak-ng # For Ubuntu
# brew install espeak-ng # For MacOS

We highly recommend using a recent version of uv for installation. If you don't have uv installed, you can install it via pip: pip install -U uv.

uv sync
uv sync --extra compile # optional but needed to run the hybrid
uv pip install -e .

uv pip install -e .
uv pip install -e .[compile] # optional but needed to run the hybrid

pip install -e .
pip install --no-build-isolation -e .[compile] # optional but needed to run the hybrid

For convenience we provide a minimal example to check that the installation works:

uv run sample.py
# python sample.py

git clone https://github.com/Zyphra/Zonos.git
cd Zonos

# For gradio
docker compose up

# Or for development you can do
docker build -t zonos .
docker run -it --gpus=all --net=host -v /path/to/Zonos:/Zonos -t zonos
cd /Zonos
python sample.py # this will generate a sample.wav in /Zonos