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ttsds/maskgct

By ttsds · ↓ 0 · ♥ 0 · Updated 2026-01-26

What's in this repo

This page lists the files in ttsds/maskgct, including poly_bert_model.onnx.

  • 1 ONNX models (.onnx files)
  • 9 files, including 6 .safetensors, 1 .md, 1 .onnx
  • Last updated 2026-01-26

ONNX files

File Size Download
vendor_assets/models/tts/maskgct/g2p/sources/g2p_chinese_model/poly_bert_model.onnx — Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

MaskGCT

This is a mirror of the original weights for use with TTSDB.

Original weights: https://huggingface.co/amphion/MaskGCT Original code: https://github.com/open-mmlab/Amphion

MaskGCT is a zero-shot text-to-speech model using a masked generative codec transformer by Amphion.

Original Work

This model was created by the original authors. Please cite their work if you use this model:

@article{wang2024maskgct,
  title={MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer},
  author={Wang, Yuancheng and Zhan, Haoyue and Liu, Liwei and Zeng, Ruihong and Guo, Haotian and Zheng, Jiachen and Zhang, Qiang and Zhang, Xueyao and Zhang, Shunsi and Wu, Zhizheng},
  journal={arXiv preprint arXiv:2409.00750},
  year={2024}
}
@inproceedings{amphion,
  author={Zhang, Xueyao and Xue, Liumeng and Gu, Yicheng and Wang, Yuancheng and Li, Jiaqi and He, Haorui and Wang, Chaoren and Song, Ting and Chen, Xi and Fang, Zihao and Chen, Haopeng and Zhang, Junan and Tang, Tze Ying and Zou, Lexiao and Wang, Mingxuan and Han, Jun and Chen, Kai and Li, Haizhou and Wu, Zhizheng},
  title={Amphion: An Open-Source Audio, Music and Speech Generation Toolkit},
  booktitle={{IEEE} Spoken Language Technology Workshop, {SLT} 2024},
  year={2024}
}

Papers:

  • https://arxiv.org/abs/2409.00750

  • https://ieeexplore.ieee.org/abstract/document/10832255

Installation

pip install ttsdb-maskgct

Usage

from ttsdb_maskgct import MaskGCT

# Load the model (downloads weights automatically)
model = MaskGCT(model_id="ttsds/MaskGCT")

# Synthesize speech
audio, sample_rate = model.synthesize(
    text="Hello, this is a test of MaskGCT.",
    reference_audio="path/to/reference.wav",
    text_reference="Transcript of the reference audio.",
    language="en",
)

# Save the output
model.save_audio(audio, sample_rate, "output.wav")

Model Details

Property Value
Sample Rate 24000 Hz
Parameters 1010M
Architecture Non-Autoregressive Masked Transformer
Languages English, Chinese, Korean, Japanese, French, German
Release Date 2024-10-17

Training Data

License

  • Weights: Creative Commons Attribution-NonCommercial 4.0
  • Code: MIT License

Please refer to the original repositories for full license terms.

Links

Model info

ttsdb onnx safetensors tts text-to-speech speech-synthesis voice-cloning eng zho kor jpn fra
↓ 0 ♥ 0

Created: 2026-01-23

Updated: 2026-01-26

View on Hugging Face

Files (9)

.gitattributes
README.md
acoustic_codec/model.safetensors
acoustic_codec/model_1.safetensors
s2a_model/s2a_model_1layer/model.safetensors
s2a_model/s2a_model_full/model.safetensors
semantic_codec/model.safetensors
t2s_model/model.safetensors
vendor_assets/models/tts/maskgct/g2p/sources/g2p_chinese_model/poly_bert_model.onnx ONNX

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