Instructions to use LunaFox/DraculaFlow-TTS-mlx-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use LunaFox/DraculaFlow-TTS-mlx-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir DraculaFlow-TTS-mlx-8bit LunaFox/DraculaFlow-TTS-mlx-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
DraculaFlow-TTS-mlx-8bit
This repository contains the 8-bit quantized MLX-converted weights for DraculaFlow-TTS, optimized for fast and memory-efficient inference on Apple Silicon using mlx-audio.
- Original Hugging Face Model: LunaFox/DraculaFlow-TTS
Installation
Install mlx-audio:
pip install mlx-audio
Usage
1. Command Line Interface (CLI)
Generate audio clips directly from the terminal using mlx_audio.tts.generate:
python -m mlx_audio.tts.generate \
--model LunaFox/DraculaFlow-TTS-mlx-8bit \
--text "We are smoking joint out of a custom carved bong." \
--voice dracula_flow \
--output_path ./output.wav
To play the audio immediately upon generation, add the --play flag:
python -m mlx_audio.tts.generate \
--model LunaFox/DraculaFlow-TTS-mlx-8bit \
--text "This shit ain't nothing to me man." \
--voice dracula_flow \
--play
2. Python API
You can also generate audio clips within a Python script:
from mlx_audio.tts.generate import generate_audio
generate_audio(
text="We are smoking joint out of a custom carved bong.",
model="LunaFox/DraculaFlow-TTS-mlx-8bit",
voice="dracula_flow",
output_path="./output.wav",
)
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