Qwen3-TTS-TBLive-Base

Qwen3-TTS-TBLive-Base

A Chinese live-streaming domain TTS checkpoint fine-tuned from Qwen3-TTS-12Hz-1.7B-Base via continual pre-training (CPT) and GRPO post-training on live-streaming speech data.

Recommended starting point for downstream fine-tuning. If you need production-ready built-in live-streaming voices, use the sibling checkpoint TaoLiveAIGC/Qwen3-TTS-TBLive-CustomVoice.

Benchmark

Zero-shot voice-cloning results on the public seed-tts-eval test sets, compared against open-source baselines. / marks numbers not reported.

Quickstart

pip install -U qwen-tts

import torch
from qwen_tts import Qwen3TTSModel

model = Qwen3TTSModel.from_pretrained(
    "TaoLiveAIGC/Qwen3-TTS-TBLive-Base",
    device_map="cuda:0",
    dtype=torch.bfloat16,
)

# Zero-shot voice cloning with a short reference audio
wavs, sr = model.generate_voice_clone(
    text="家人们，今天直播间的福利真的拉满了！",
    language="Chinese",
    ref_audio="path/to/reference.wav",
    ref_text="参考音频对应的文本",
)

For training pipelines (SFT / GRPO), inference post-selection, and advanced usage, see the companion training repository. For upstream features (vLLM serving, DashScope API, deployment), refer to the upstream Qwen3-TTS repository.

Checkpoint contents

├── model.safetensors            # main checkpoint (~3.6 GB)
├── config.json / configuration.json / generation_config.json
├── preprocessor_config.json
├── tokenizer_config.json / vocab.json / merges.txt
└── speech_tokenizer/            # 12 Hz speech tokenizer (~651 MB, same as upstream)

License

Released under the Apache License 2.0, consistent with upstream Qwen3-TTS.

Acknowledgements

Our sincere thanks to the Qwen team for open-sourcing Qwen3-TTS — the base model, tokenizer, and reference training / inference code that make this work possible.