Instructions to use KeythSullivan/neutts-air with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use KeythSullivan/neutts-air with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="KeythSullivan/neutts-air", filename="neutss-air-BF16.gguf", )
llm.create_chat_completion( messages = "\"The answer to the universe is 42\"" )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use KeythSullivan/neutts-air with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf KeythSullivan/neutts-air:BF16 # Run inference directly in the terminal: llama-cli -hf KeythSullivan/neutts-air:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf KeythSullivan/neutts-air:BF16 # Run inference directly in the terminal: llama-cli -hf KeythSullivan/neutts-air:BF16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf KeythSullivan/neutts-air:BF16 # Run inference directly in the terminal: ./llama-cli -hf KeythSullivan/neutts-air:BF16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf KeythSullivan/neutts-air:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf KeythSullivan/neutts-air:BF16
Use Docker
docker model run hf.co/KeythSullivan/neutts-air:BF16
- LM Studio
- Jan
- Ollama
How to use KeythSullivan/neutts-air with Ollama:
ollama run hf.co/KeythSullivan/neutts-air:BF16
- Unsloth Studio new
How to use KeythSullivan/neutts-air with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for KeythSullivan/neutts-air to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for KeythSullivan/neutts-air to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for KeythSullivan/neutts-air to start chatting
- Pi new
How to use KeythSullivan/neutts-air with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf KeythSullivan/neutts-air:BF16
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "KeythSullivan/neutts-air:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use KeythSullivan/neutts-air with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf KeythSullivan/neutts-air:BF16
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default KeythSullivan/neutts-air:BF16
Run Hermes
hermes
- Docker Model Runner
How to use KeythSullivan/neutts-air with Docker Model Runner:
docker model run hf.co/KeythSullivan/neutts-air:BF16
- Lemonade
How to use KeythSullivan/neutts-air with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull KeythSullivan/neutts-air:BF16
Run and chat with the model
lemonade run user.neutts-air-BF16
List all available models
lemonade list
File size: 7,054 Bytes
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license: apache-2.0
pipeline_tag: text-to-speech
tags:
- audio
- speech
- speech-language-models
datasets:
- amphion/Emilia-Dataset
- neuphonic/emilia-yodas-english-neucodec
---
# NeuTTS Air ☁️
[](https://www.youtube.com/watch?v=YAB3hCtu5wE)
[🚀 Spaces Demo](https://huggingface.co/spaces/neuphonic/neutts-air), [🔧 Github](https://github.com/neuphonic/neutts-air)
[Q8 GGUF version](https://huggingface.co/neuphonic/neutts-air-q8-gguf), [Q4 GGUF version](https://huggingface.co/neuphonic/neutts-air-q4-gguf)
*Created by [Neuphonic](http://neuphonic.com/) - building faster, smaller, on-device voice AI*
State-of-the-art Voice AI has been locked behind web APIs for too long. NeuTTS Air is the world’s first super-realistic, on-device, TTS speech language model with instant voice cloning. Built off a 0.5B LLM backbone, NeuTTS Air brings natural-sounding speech, real-time performance, built-in security and speaker cloning to your local device - unlocking a new category of embedded voice agents, assistants, toys, and compliance-safe apps.
## Key Features
- 🗣Best-in-class realism for its size - produces natural, ultra-realistic voices that sound human
- 📱Optimised for on-device deployment - provided in GGML format, ready to run on phones, laptops, or even Raspberry Pis
- 👫Instant voice cloning - create your own speaker with as little as 3 seconds of audio
- 🚄Simple LM + codec architecture built off a 0.5B backbone - the sweet spot between speed, size, and quality for real-world applications
> [!CAUTION]
> Websites like neutts.com are popping up and they're not affliated with Neuphonic, our github or this repo.
>
> We are on neuphonic.com only. Please be careful out there! 🙏
## Model Details
NeuTTS Air is built off Qwen 0.5B - a lightweight yet capable language model optimised for text understanding and generation - as well as a powerful combination of technologies designed for efficiency and quality:
- **Audio Codec**: [NeuCodec](https://huggingface.co/neuphonic/neucodec) - our proprietary neural audio codec that achieves exceptional audio quality at low bitrates using a single codebook
- **Format**: Available in GGML format for efficient on-device inference
- **Responsibility**: Watermarked outputs
- **Inference Speed**: Real-time generation on mid-range devices
- **Power Consumption**: Optimised for mobile and embedded devices
## Get Started with NeuTTS
1. **Install System Dependencies (required): `espeak-ng`**
> [!NOTE]
> With `brew` on macOS Ventura and later, `apt` in Ubuntu version 25 or Debian version 13, and `choco`/`winget` on Windows, install the latest version of `espeak-ng` with the commands below. If you have a different or older operating system, you may need to install from source: see the following link https://github.com/espeak-ng/espeak-ng/blob/master/docs/building.md
Please refer to the following link for instructions on how to install `espeak-ng`:
https://github.com/espeak-ng/espeak-ng/blob/master/docs/guide.md
```bash
# Mac OS
brew install espeak-ng
# Ubuntu/Debian
sudo apt install espeak-ng
# Windows install
# via chocolatey (https://community.chocolatey.org/packages?page=1&prerelease=False&moderatorQueue=False&tags=espeak)
choco install espeak-ng
# via winget
winget install -e --id eSpeak-NG.eSpeak-NG
# via msi (need to add to path or folow the "Windows users who installed via msi" below)
# find the msi at https://github.com/espeak-ng/espeak-ng/releases
```
Windows users who installed via msi / do not have their install on path need to run the following (see https://github.com/bootphon/phonemizer/issues/163)
```pwsh
$env:PHONEMIZER_ESPEAK_LIBRARY = "c:\Program Files\eSpeak NG\libespeak-ng.dll"
$env:PHONEMIZER_ESPEAK_PATH = "c:\Program Files\eSpeak NG"
setx PHONEMIZER_ESPEAK_LIBRARY "c:\Program Files\eSpeak NG\libespeak-ng.dll"
setx PHONEMIZER_ESPEAK_PATH "c:\Program Files\eSpeak NG"
```
2. **Install NeuTTS**
```bash
pip install neutts
```
Or for a local editable install, clone the [neutts repository](https://github.com/neuphonic/neutts) and run in the base folder:
```bash
pip install -e .
```
Alternatively to install all dependencies, including `onnxruntime` and `llama-cpp-python` (equivalent to steps 3 and 4 below):
```bash
pip install neutts[all]
```
or for an editable install:
```bash
pip install -e .[all]
```
3. **(Optional) Install `llama-cpp-python` to use `.gguf` models.**
```bash
pip install "neutts[llama]"
```
Note that this installs `llama-cpp-python` without GPU support. To install with GPU support (e.g., CUDA, MPS) please refer to:
https://pypi.org/project/llama-cpp-python/
4. **(Optional) Install `onnxruntime` to use the `.onnx` decoder.**
```bash
pip install "neutts[onnx]"
```
## **Basic Example**
Run the basic example script to synthesize speech:
```bash
python -m examples.basic_example \
--input_text "My name is Dave, and um, I'm from London" \
--ref_audio samples/dave.wav \
--ref_text samples/dave.txt
```
To specify a particular model repo for the backbone or codec, add the `--backbone` argument. Available backbones are listed in [NeuTTS-Air huggingface collection](https://huggingface.co/collections/neuphonic/neutts-air-68cc14b7033b4c56197ef350).
Several examples are available, including a Jupyter notebook in the `examples` folder.
### **Simple One-Code Block Usage**
```python
from neutts import NeuTTS
import soundfile as sf
tts = NeuTTS(backbone_repo="neuphonic/neutts-air-q4-gguf", backbone_device="cpu", codec_repo="neuphonic/neucodec", codec_device="cpu")
input_text = "My name is Dave, and um, I'm from London."
ref_text = "samples/dave.txt"
ref_audio_path = "samples/dave.wav"
ref_text = open(ref_text, "r").read().strip()
ref_codes = tts.encode_reference(ref_audio_path)
wav = tts.infer(input_text, ref_codes, ref_text)
sf.write("test.wav", wav, 24000)
```
# Tips
NeuTTS Air requires two inputs:
1. A reference audio sample (`.wav` file)
2. A text string
The model then synthesises the text as speech in the style of the reference audio. This is what enables NeuTTS Air’s instant voice cloning capability.
### Example Reference Files
You can find some ready-to-use samples in the `examples` folder:
- `samples/dave.wav`
- `samples/jo.wav`
### Guidelines for Best Results
For optimal performance, reference audio samples should be:
1. **Mono channel**
2. **16-44 kHz sample rate**
3. **3–15 seconds in length**
4. **Saved as a `.wav` file**
5. **Clean** — minimal to no background noise
6. **Natural, continuous speech** — like a monologue or conversation, with few pauses, so the model can capture tone effectively
# **Responsibility**
Every audio file generated by NeuTTS Air includes [**Perth (Perceptual Threshold) Watermarker](https://github.com/resemble-ai/perth).**
# **Disclaimer**
Don't use this model to do bad things… please. |