Instructions to use fluxions/vui with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Vui
How to use fluxions/vui with Vui:
# !pip install git+https://github.com/fluxions-ai/vui import torchaudio from vui.inference import render from vui.model import Vui, model = Vui.from_pretrained().cuda() waveform = render( model, "Hey, here is some random stuff, usually something quite long as the shorter the text the less likely the model can cope!", ) print(waveform.shape) torchaudio.save("out.opus", waveform[0], 22050) - Notebooks
- Google Colab
- Kaggle
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license: mit
language:
- en
pipeline_tag: text-to-speech
library_name: vui
vui
https://github.com/fluxions-ai/vui
Small Conversational speech models that can run on device
Installation
uv pip install -e .
Demo
python demo.py
Models
Vui.BASE is base checkpoint trained on 40k hours of audio conversations Vui.ABRAHAM is a single speaker model that can reply with context awareness. Vui.COHOST is checkpoint with two speakers that can talk to each other.
Voice Cloning
You can clone with the base model quite well but it's not perfect as hasn't seen that much audio / wasn't trained for long
FAQ
- Was developed with on two 4090's https://x.com/harrycblum/status/1752698806184063153
- Hallucinations: yes the model does hallucinate, but this is the best I could do with limited resources! :(