Instructions to use mlx-community/Soprano-1.1-80M-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Soprano-1.1-80M-6bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/Soprano-1.1-80M-6bit --local-dir Soprano-1.1-80M-6bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from mlx-community/Soprano-1.1-80M-6bit: direct link, hf CLI and curl.
- Browser
- Download file 1.1 kB
-
https://huggingface.co/mlx-community/Soprano-1.1-80M-6bit/resolve/main/README.md
- Command line
-
hf download hf://mlx-community/Soprano-1.1-80M-6bit/README.md
-
curl -L -o README.md https://huggingface.co/mlx-community/Soprano-1.1-80M-6bit/resolve/main/README.md
1.1 kB
metadata
base_model: ekwek/Soprano-1.1-80M
library_name: mlx-audio
pipeline_tag: text-to-speech
tags:
- mlx
- text-to-speech
- speech
- tts
- mlx
- text-to-speech
- speech
- speech generation
- voice cloning
- tts
- mlx-audio
mlx-community/Soprano-1.1-80M-6bit
This model was converted to MLX format from mlx-community/Soprano-1.1-80M-bf16 using mlx-audio version 0.3.1.
Refer to the original model card for more details on the model.
Use with mlx-audio
pip install -U mlx-audio
CLI Example:
python -m mlx_audio.tts.generate --model mlx-community/Soprano-1.1-80M-6bit --text "Hello, this is a test."
Python Example:
from mlx_audio.tts.utils import load_model
from mlx_audio.tts.generate import generate_audio
model = load_model("mlx-community/Soprano-1.1-80M-6bit")
generate_audio(
model=model,
text="Hello, this is a test.",
ref_audio="path_to_audio.wav",
file_prefix="test_audio",
)