# Faster Whisper

> 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".

- Skill: `johnalbertini14-glitch/faster-whisper-2` (Agent Skill, multi-file: 5 files)
- Install (CLI): `npx skillmds@latest add johnalbertini14-glitch/faster-whisper-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/johnalbertini14-glitch/faster-whisper-2/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Docs & Writing
- Author: johnalbertini14-glitch (https://skillmd.com/u/johnalbertini14-glitch)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/johnalbertini14-glitch/faster-whisper-2

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# 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.

```bash
./setup.sh
```

Requirements:
- Python 3.10 or later
- ffmpeg (installed on the system)

## Usage

Use the transcription script to process audio files.

### Basic Transcription
```bash
./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`.