Text-to-Speech
MLX
Safetensors
llama
speech-synthesis
multilingual
indic
orpheus
snac
mlx-audio
4-bit precision
Instructions to use mlx-community/svara-tts-v1-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/svara-tts-v1-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir svara-tts-v1-4bit mlx-community/svara-tts-v1-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Xet hash:
- 943eac2190bc841b30bc637b3c40b86087d790464f6a459cdb3cabe8b76443ef
- Size of remote file:
- 22.8 MB
- SHA256:
- 044e2a10201774018db120391980464472baabf223bd353cea49b17da0b66abc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.