Qwen3 Tts Vocence Sft Epoch1

--- license: apache-2.0 pipeline_tag: text-to-speech library_name: qwen-tts tags: - audio - tts - qwen - multilingual --- # Qwen3-TTS <br> <p align="center"> <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen3-TTS-Repo/qwen3_tts_logo.png" width="400"/> <p> <p align="center"> &nbsp&nbsp🤗 <a href="https://huggingface.co/collections/Qwen/qwen3-tts">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/collections/Qwen/Qwen3-TTS">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://qwen.ai/blog?id=qwen3tts-0115">Blog</a>&nbsp&nbsp | &nbsp&nbsp📑 <a href="https://huggingface.co/papers/2601.15621">Paper</a>&nbsp&nbsp | &nbsp&nbsp💻 <a href="https://github.com/QwenLM/Qwen3-TTS">GitHub</a> </p> We release **Qwen3-TTS**, a series of powerful speech generation models developed by Qwen, offering comprehensive support for voice cloning, voice design, ultra-high-quality human-like speech generation, and natural language-based voice control. ## Overview Qwen3-TTS covers 10 major languages (Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian) as well as multiple dialectal voice profiles. Key features: * **Powerful Speech Representation**: Powered by the self-developed Qwen3-TTS-Tokenizer-12Hz, it achieves efficient acoustic compression and high-dimensional semantic modeling. * **Universal End-to-End Architecture**: Utilizing a discrete multi-codebook LM architecture to bypass traditional information bottlenecks. * **Extreme Low-Latency Streaming Generation**: Supports streaming generation with end-to-end synthesis latency as low as 97ms. * **Intelligent Voice Control**: Supports speech generation driven by natural language instructions for flexible control over timbre, emotion, and prosody. ## Quickstart ### Environment Setup Install the `qwen-tts` Python package from PyPI: ```bash pip install -U qwen-tts ``` ### Python Package Usage ```python import torch import soundfile as sf from qwen_tts import Qwen3TTSModel # Load the model model = Qwen3TTSModel.from_pretrained( "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice", device_map="cuda:0", dtype=torch.bfloat16, attn_implementation="flash_attention_2", ) # Custom Voice Generation wavs, sr = model.generate_custom_voice( text="其实我真的有发现，我是一个特别善于观察别人情绪的人。", language="Chinese", speaker="Vivian", instruct=...