Audio-to-Audio
Transformers
Safetensors
Qwen3-TTS
English
text-generation
zen
zenlm
hanzo
dubbing
speech
audio
real-time
Instructions to use zenlm/zen-dub-live with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenlm/zen-dub-live with Transformers:
# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("zenlm/zen-dub-live", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Zen Dub Live
Real-time voice dubbing model for live translation and audio localization.
Overview
Built on Zen MoDE (Mixture of Distilled Experts) architecture with 1B parameters.
Developed by Hanzo AI and the Zoo Labs Foundation.
Quick Start
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])
Model Details
| Attribute | Value |
|---|---|
| Parameters | 1B |
| Architecture | Zen MoDE |
| Context | 30s audio |
| License | Apache 2.0 |
License
Apache 2.0
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