Instructions to use mlx-community/Llama-OuteTTS-1.0-1B-fp16 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-fp16 with OuteTTS:
import outetts enum = outetts.Models("mlx-community/Llama-OuteTTS-1.0-1B-fp16".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-fp16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Llama-OuteTTS-1.0-1B-fp16 mlx-community/Llama-OuteTTS-1.0-1B-fp16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 267 Bytes
75be552 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"_from_model_config": true,
"bos_token_id": 133309,
"eos_token_id": 133310,
"pad_token_id": 128001,
"transformers_version": "4.48.3",
"do_sample": true,
"temperature": 0.4,
"repetition_penalty": 1.1,
"top_k": 40,
"top_p": 0.9,
"min_p": 0.05
}
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