Instructions to use Charles322/TTS_Arm64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Charles322/TTS_Arm64 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download Charles322/TTS_Arm64 --local-dir TTS_Arm64
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
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Download README.md from Charles322/TTS_Arm64: direct link, hf CLI and curl.
- Browser
- Download file 536 Bytes
-
https://huggingface.co/Charles322/TTS_Arm64/resolve/main/README.md
- Command line
-
hf download hf://Charles322/TTS_Arm64/README.md
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curl -L -o README.md https://huggingface.co/Charles322/TTS_Arm64/resolve/main/README.md
536 Bytes
metadata
license: apache-2.0
language:
- en
base_model:
- yl4579/StyleTTS2-LJSpeech
pipeline_tag: text-to-speech
library_name: mlx
mlx-community/Kokoro-82M-bf16
This model was converted to MLX format from hexagrad/Kokoro-82M using mlx-audio version 0.0.1.
Refer to the original model card for more details on the model.
Use with mlx
pip install -U mlx-audio
python -m mlx_audio.tts.generate --model mlx-community/Kokoro-82M-bf16 --text "Hello world"