qwen3-tts-endpoint

Qwen3-TTS CustomVoice — HF Inference Endpoint

Custom handler.py that serves Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice on a dedicated HF Inference Endpoint via the official qwen-tts package.

The handler loads the 1.9B model + the 12Hz speech tokenizer (vocoder) at cold start and exposes one POST route returning base64 WAV (24kHz mono).

Request

{
  "inputs": "She watched the rain trace lines down the window.",
  "parameters": {
    "speaker": "Ryan",
    "language": "English",
    "instruct": "calm, observational"
  }
}

Zero-shot clone (best-effort on CustomVoice; the -Base model is better for this):

{
  "inputs": "text in the cloned voice",
  "parameters": {
    "language": "English",
    "ref_audio_b64": "<base64 wav/mp3>",
    "ref_text": "exact transcript of the reference clip"
  }
}

Response: [{"audio": "<base64 wav>", "format": "wav", "sample_rate": 24000, "duration_s": 3.1, "speaker": "Ryan", "language": "English"}]

Built-in speakers

Languages: Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian (or Auto).

Recommended instance

nvidia-l4 x1 (24 GB) is comfortable — the model is ~4 GB in bf16. Cold start ~3-6 min (pip build + model + vocoder download + load). flash-attn is deliberately omitted; the handler uses sdpa.

Lifecycle (from the video_lab repo)

python scripts/_run_qwen_tts_endpoint.py --start    # create + wait for ready
python scripts/_run_qwen_tts_endpoint.py --status   # show state + URL
python scripts/_run_qwen_tts_endpoint.py --stop     # delete (full teardown)