Instructions to use mlx-community/Llama-OuteTTS-1.0-1B-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OuteTTS
How to use mlx-community/Llama-OuteTTS-1.0-1B-8bit with OuteTTS:
import outetts enum = outetts.Models("mlx-community/Llama-OuteTTS-1.0-1B-8bit".split("/", 1)[1]) # VERSION_1_0_SIZE_1B cfg = outetts.ModelConfig.auto_config(enum, outetts.Backend.HF) tts = outetts.Interface(cfg) speaker = tts.load_default_speaker("EN-FEMALE-1-NEUTRAL") tts.generate( outetts.GenerationConfig( text="Hello there, how are you doing?", speaker=speaker, ) ).save("output.wav") - MLX
How to use mlx-community/Llama-OuteTTS-1.0-1B-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Llama-OuteTTS-1.0-1B-8bit mlx-community/Llama-OuteTTS-1.0-1B-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
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