Modelpublic

OpenVoiceOS/phoonnx-qwen3-tts

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face

0likes21downloads

Model Card

phoonnx-qwen3-tts

ONNX export of Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice for phoonnx. The weights, the architecture and the nine timbres are the work of the Alibaba Qwen team; this repository only holds the graphs in ONNX form, converted with the script in scripts/conversion/qwen3tts/.

Graphs

File	What it does
`talker.onnx`	28-layer talker, one KV-cached step per 80 ms frame
`text_embed.onnx`	text ids to projected text hidden states
`codec_embed.onnx`	talker codec ids to hidden states
`code_predictor_prefill.onnx`	talker hidden plus code group 0, gives group 1
`code_predictor_step.onnx`	code group n gives code group n+1
`sub_codec_embed.onnx`	code-group token to its group's embedding
`codec_decoder.onnx`	16 code groups per frame to 24 kHz audio
`tokenizer.json`	the model's own Qwen2 subword BPE

All graphs are float32, opset 17 (18 for the codec decoder).

Parity

Checked against the upstream PyTorch model on CPU with greedy decoding:

Measurement	Result
Prompt embeddings, max abs diff	2.4e-07
Talker prefill logits, max abs diff	2.3e-05
Talker decode logits, max abs diff	5.0e-05
Greedy token agreement, 52 frames x 16 groups	100 % (832/832)
Codec decoder waveform, max abs diff	9.9e-07

Voices

Nine timbres: vivian, serena, uncle_fu, dylan (Beijing), eric (Sichuan), ryan, aiden, ono_anna, sohee. Ten languages: Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian.

Use

python

from phoonnx.model_manager import TTSModelManager

manager = TTSModelManager()
manager.merge_default_voices()
voice = manager.voices["qwen3tts/ryan/en"].load()
for chunk in voice.synthesize("The quick brown fox jumps over the lazy dog."):
    ...  # chunk.audio_float_array

Licence

Apache-2.0, the licence of the original model. Cite the Qwen3-TTS technical report (arXiv 2601.15621) when you use these weights.