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Local Llama TTS

Local text-to-speech using llama-tts (llama.cpp) and OuteTTS-1.0-0.6B model.

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name: local-llama-tts description: Local text-to-speech using llama-tts (llama.cpp) and OuteTTS-1.0-0.6B model. metadata: { "openclaw": { "emoji": "🔊", "requires": { "bins": ["llama-tts"] }, }, }

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

  1. Model: Download from OuteAI/OuteTTS-1.0-0.6B-GGUF
  2. 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

如何使用「Local Llama TTS」?

  1. 打开小龙虾AI(Web 或 iOS App)
  2. 点击上方「立即使用」按钮,或在对话框中输入任务描述
  3. 小龙虾AI 会自动匹配并调用「Local Llama TTS」技能完成任务
  4. 结果即时呈现,支持继续对话优化

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