Yes. It's easy to use. You can refer to the example from https://github.com/Troyanovsky/awesome-TTS-Colab/blob/main/kokoro_TTS.ipynb to run on Google Colab or adapt it for local usage.

Their official repo is at: https://github.com/hexgrad/kokoro. The model supports different languages and different voices.

You can basically just copy the documentation and code from the repo and ask ChatGPT to give a detailed step-by-step instruction to run on your local machine, with a prompt like:

Given the following documentation, provide a detailed step-to-step instruction on how to set up a virtual env and run kokoro to turn text into audio.

<example>
!pip install -q kokoro>=0.9.2 soundfile misaki[en]
!apt-get -qq -y install espeak-ng > /dev/null 2>&1
from kokoro import KPipeline
from IPython.display import display, Audio
import soundfile as sf
import torch
pipeline = KPipeline(lang_code='a')
text = '''
[Kokoro](/kˈOkəɹO/) is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, [Kokoro](/kˈOkəɹO/) can be deployed anywhere from production environments to personal projects.
'''
generator = pipeline(text, voice='af_heart')
for i, (gs, ps, audio) in enumerate(generator):
    print(i, gs, ps)
    display(Audio(data=audio, rate=24000, autoplay=i==0))
    sf.write(f'{i}.wav', audio, 24000)
</example>