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fantaxy/neutts-air
neutts-air is a text-to-speech model from fantaxy. Use it when you need text read aloud. The card lists the license as apache-2.0.
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Downloads · 30 days
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.gguf1.5 GB · 49%
From the Hugging Face model README
Q8 GGUF version, Q4 GGUF version
Created by Neuphonic - 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.
[!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! 🙏
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:
Clone the Git Repo
git clone https://github.com/neuphonic/neutts-air.git
cd neuttsair
Install espeak (required dependency)
Please refer to the following link for instructions on how to install espeak:
https://github.com/espeak-ng/espeak-ng/blob/master/docs/guide.md
# Mac OS
brew install espeak
# Ubuntu/Debian
sudo apt install espeak
# Arch Linux
paru -S aur/espeak
Install Python dependencies
The requirements file includes the dependencies needed to run the model with PyTorch. When using an ONNX decoder or a GGML model, some dependencies (such as PyTorch) are no longer required.
The inference is compatible and tested on python>=3.11.
pip install -r requirements.txt
Run the basic example script to synthesize speech:
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.
Several examples are available, including a Jupyter notebook in the examples folder.
from neuttsair.neutts import NeuTTSAir
import soundfile as sf
tts = NeuTTSAir( 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)
NeuTTS Air requires two inputs:
.wav file)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.
You can find some ready-to-use samples in the examples folder:
samples/dave.wavsamples/jo.wavFor optimal performance, reference audio samples should be:
.wav fileEvery audio file generated by NeuTTS Air includes **Perth (Perceptual Threshold) Watermarker.**
Don't use this model to do bad things… please.