Docker offers the quickest path to setting up this model locally.
Simply follow the directions outlined below.
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No manual effort needed; the setup auto-ingests the large data.
You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.
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🧩 Hash sum → 1bb4a16faaa7e45dbfcd01e980ce7ff8 — Update date: 2026-06-24
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Qwen3-TTS-12Hz-1.7B-CustomVoice is a cutting‑edge text‑to‑speech model that delivers high‑fidelity voice synthesis at a 12 Hz frame rate. It supports custom voice cloning, allowing users to train on just a few samples and generate personalized speech that retains the speaker’s unique characteristics. Its 1.7 B parameter architecture balances performance with a low memory footprint, making it suitable for deployment on consumer‑grade hardware. Inference latency stays under 50 ms per utterance, enabling real‑time applications such as interactive assistants and live dubbing. The model has been optimized for multiple languages and prosodic styles, producing natural‑sounding output across a wide range of domains.
| Spec | Value |
|---|---|
| Parameter Count | 1.7 B |
| Sample Rate | 12 Hz (frame) |
| Training Data | 200 h multi‑speaker speech |
| Latency | <50 ms |
| Supported Languages | 20+ |
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