Text-to-Speech
Transformers
Safetensors
Qwen3-TTS
English
Chinese
text-generation
zen3
zen3-tts
zenlm
qwen3-tts
speech-synthesis
edge
low-latency
12hz
Instructions to use zenlm/zen3-tts-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenlm/zen3-tts-0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="zenlm/zen3-tts-0.6B")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("zenlm/zen3-tts-0.6B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2770552d9ac6119e00cc15f368f2e08a4ae4787b1f94234e639af510f8eb2ea0
- Size of remote file:
- 682 MB
- SHA256:
- 836b7b357f5ea43e889936a3709af68dfe3751881acefe4ecf0dbd30ba571258
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.