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zenlm/zen-dub-live
zen-dub-live is a audio-to-audio model from zenlm. Use it for the audio-to-audio task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
Real-time voice dubbing model for live translation and audio localization.
Downloads · 30 days
19
9% of all-time downloads
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.safetensors4.5 GB · 100%
From the Hugging Face model README
Real-time voice dubbing model for live translation and audio localization.
Fine-tuned from Qwen3-TTS-12Hz-1.7B-Base (Apache-2.0) with Hanzo identity + agentic-data training + abliteration.
Developed by Hanzo AI and the Zoo Labs Foundation.
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor
import torch
model_id = "zenlm/zen-dub-live"
processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForSpeechSeq2Seq.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
# Load audio
import librosa
audio, sr = librosa.load("audio.wav", sr=16000)
inputs = processor(audio, sampling_rate=sr, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs)
print(processor.batch_decode(outputs, skip_special_tokens=True)[0])
| Attribute | Value |
|---|---|
| Base model | Qwen/Qwen3-TTS-12Hz-1.7B-Base |
| Parameters | ~1.9B (Qwen3-TTS 1.7B core) |
| Architecture | Qwen3-TTS (Qwen3TTSForConditionalGeneration) |
| Context | 30s audio |
| License | Apache 2.0 |
Fine-tuned from Qwen/Qwen3-TTS-12Hz-1.7B-Base, developed by the Qwen team (Alibaba) and released under the Apache 2.0 license. Hanzo adds identity training, agentic-data fine-tuning, and abliteration on top of the upstream weights.
Apache 2.0 — inherited from the upstream Qwen3-TTS-12Hz-1.7B-Base base model.