Model Details
Full Model IDk2-fsa/OmniVoice
Pipeline / Tasktext-to-speech
Libraryomnivoice
Downloads (all-time)2.0M
Likes1.6K
Last Modified7/3/2026
Author / Orgk2-fsa
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-to-speech", model="k2-fsa/OmniVoice")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
omnivoicesafetensorszero-shotmultilingualvoice-cloningvoice-designtext-to-speechaaeaalaaoababbabnabrabsabvacmacwacxadfadxadyaebaecafafbafoahlahsajg
More text-to-speech Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: text-to-speech
This model is designed for the text-to-speech task. Explore more models for this use case.
All text-to-speech Models →📊 Popularity
⬇ Downloads2.0M
❤️ Community Likes1.6K
🛠️ Requirements
- →Install: pip install omnivoice
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.