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Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
talker.model.codec_embedding.weight
2,048
bfloat16
{ "aiden": { "id": 2861, "gender": "m", "lang": "en,zh" }, "dylan": { "id": 2878, "gender": "m", "lang": "en,zh" }, "eric": { "id": 2875, "gender": "m", "lang": "en,zh" }, "ono_anna": { "id": 2873, "gender": "f", "lang": "ja,en,zh" }, "ryan": { "id":...
Lifted rows from CustomVoice codec_embedding. Consumed as VoiceClonePromptItem(ref_spk_embedding=row, x_vector_only_mode=True).

Qwen3-TTS preset voice embeddings

The 9 named speakers from Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice packaged as a small sidecar bundle usable with the -Base checkpoint.

  • bundle.safetensors — 9 × 2048-d bfloat16 rows, ~37 KB total
  • bundle.json — metadata (speaker name → spk_id, gender, supported languages)

Each row is lifted from talker.model.codec_embedding.weight in the CustomVoice checkpoint at the speaker-ID index from its config.json. With these rows, you can:

  1. Deploy only Qwen/Qwen3-TTS-12Hz-1.7B-Base (no need to download the CustomVoice checkpoint separately)
  2. Use the named voices via the standard voice-cloning API path

Usage

from safetensors.torch import load_file
from qwen_tts import VoiceClonePromptItem

rows = load_file("bundle.safetensors")  # dict[str, Tensor(2048,)]

item = VoiceClonePromptItem(
    ref_code=None,
    ref_spk_embedding=rows["vivian"].cuda().bfloat16(),
    x_vector_only_mode=True,
    icl_mode=False,
    ref_text=None,
)
wavs, sr = base_model.generate_voice_clone(
    text="Hello, world.", language="English", voice_clone_prompt=[item],
)

Provenance & validation

Audio A/B comparisons — CustomVoice native vs -Base with lifted row — are published as a separate dataset: malaiwah/qwen3-tts-customvoice-ab-clips. Writeup and discussion: Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice community thread #45.

Speakers

name spk_id gender languages
aiden 2861 m en,zh
dylan 2878 m en,zh
eric 2875 m en,zh
ono_anna 2873 f ja,en,zh
ryan 3061 m en,zh
serena 3066 f en,zh
sohee 2864 f ko,en,zh
uncle_fu 3010 m zh
vivian 3065 f en,zh
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