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
| { | |
| "_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 | |
| } | |