- name
- local-llama-tts
- description
- Local text-to-speech using llama-tts (llama.cpp) and OuteTTS-1.0-0.6B model.
- metadata
Local Llama TTS
Synthesize speech locally using llama-tts and the OuteTTS-1.0-0.6B model.
Usage
You can use the wrapper script:
scripts/tts-local.sh [options] "<text>"
Options
-o, --output <file>: Output WAV file (default:output.wav)-s, --speaker <file>: Speaker reference file (optional)-t, --temp <value>: Temperature (default:0.4)
Scripts
- Location:
scripts/tts-local.sh(inside skill folder) - Model:
/data/public/machine-learning/models/text-to-speach/OuteTTS-1.0-0.6B-Q4_K_M.gguf - Vocoder:
/data/public/machine-learning/models/text-to-speach/WavTokenizer-Large-75-Q4_0.gguf - GPU: Enabled via
llama-tts.
Setup
- Model: Download from OuteAI/OuteTTS-1.0-0.6B-GGUF
- Vocoder: Download from ggml-org/WavTokenizer (Note: Felix uses a Q4_0 version, Q5_1 is linked here as a high-quality alternative).
Place files in /data/public/machine-learning/models/text-to-speach/ or update scripts/tts-local.sh.
Sampling Configuration
The model card recommends the following settings (hardcoded in the script):
- Temperature: 0.4
- Repetition Penalty: 1.1
- Repetition Range: 64
- Top-k: 40
- Top-p: 0.9
- Min-p: 0.05