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// Skill profile

Faster-Whisper

name: faster-whisper

by damirikys · published 2026-03-22

数据处理自动化任务
Total installs
0
Stars
★ 0
Last updated
2026-03
// Install command
$ claw add gh:damirikys/damirikys-faster-whisper-local
View on GitHub
// Full documentation

---

name: faster-whisper

description: Local speech-to-text using faster-whisper. High-performance transcription with GPU acceleration support. Includes word-level timestamps and distilled models. Use when asked to "transcribe audio", "whisper", or "speech to text".

metadata:

{

"openclaw":

{

"requires":

{

"bins": ["ffmpeg", "python3"],

"pip": ["faster-whisper", "torch"],

},

},

}

---

# Faster-Whisper

High-performance local speech-to-text using faster-whisper.

Setup

1. Run Setup Script

Execute the setup script to create a virtual environment and install dependencies. It will automatically detect NVIDIA GPUs for CUDA acceleration.

./setup.sh

Requirements:

  • Python 3.10 or later
  • ffmpeg (installed on the system)
  • Usage

    Use the transcription script to process audio files.

    Basic Transcription

    ./scripts/transcribe audio.mp3

    Advanced Options

  • **Specific Model**: `./scripts/transcribe audio.mp3 --model large-v3-turbo`
  • **Word Timestamps**: `./scripts/transcribe audio.mp3 --word-timestamps`
  • **JSON Output**: `./scripts/transcribe audio.mp3 --json`
  • **VAD (Silence Removal)**: `./scripts/transcribe audio.mp3 --vad`
  • Available Models

  • `distil-large-v3` (default): Best balance of speed and accuracy.
  • `large-v3-turbo`: Recommended for multilingual or highest accuracy tasks.
  • `medium.en`, `small.en`: Faster, English-only versions.
  • Troubleshooting

  • **No GPU detected**: Ensure NVIDIA drivers and CUDA are correctly installed. CPU transcription is significantly slower.
  • **OOM Error**: Use a smaller model (e.g., `small` or `base`) or use `--compute-type int8`.
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