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Faster Whisper Local
作者
Damir Armanov
· GitHub ↗
· v1.0.0
973
总下载
2
收藏
5
当前安装
1
版本数
在 OpenClaw 中安装
/install faster-whisper-local
功能描述
Local speech-to-text using faster-whisper. High-performance transcription with GPU acceleration support. Includes word-level timestamps and distilled models....
使用说明 (SKILL.md)
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.,
smallorbase) or use--compute-type int8.
安全使用建议
This skill appears to be what it says: a local transcription tool that sets up a Python virtual environment and installs faster-whisper and PyTorch. Before installing: (1) review and run the setup.sh in an isolated environment (container or dedicated machine) if you don't trust the source; (2) be aware pip will download and run third-party packages and the model weights (large download); (3) ensure ffmpeg and Python 3.10+ are installed from trusted system/package sources; (4) if you need extra assurance, create the venv manually and inspect requirements.txt and the scripts before running pip; (5) there's no evidence the skill exfiltrates data or asks for credentials, but transcriptions you run are processed locally — avoid running sensitive audio unless you control the host.
功能分析
Type: OpenClaw Skill
Name: faster-whisper-local
Version: 1.0.0
The OpenClaw skill bundle for 'faster-whisper-local' is benign. The `setup.sh` script correctly sets up a Python virtual environment, installs necessary dependencies including platform-optimized PyTorch (with CUDA support if a GPU is detected), and ensures `ffmpeg` is available. The `scripts/transcribe.py` handles audio transcription using the installed `faster-whisper` library, processing user-provided audio files and outputting text or JSON. All actions are directly aligned with the stated purpose of local speech-to-text, and there is no evidence of data exfiltration, malicious execution, persistence mechanisms, or prompt injection attempts against the agent in `SKILL.md`.
能力评估
Purpose & Capability
Name/description (local faster-whisper STT) match the requested binaries (python3, ffmpeg), the Python dependencies (faster-whisper, torch), and the included scripts. Nothing requested (no cloud credentials, no unrelated binaries) is out of scope for a local transcription tool.
Instruction Scope
SKILL.md directs running setup.sh and scripts/transcribe.py to transcribe local audio files. The scripts check local system state (python version, ffmpeg, nvidia-smi, /proc/version for WSL) to detect GPUs — this is expected for enabling acceleration and is limited to local environment checks. There are no instructions to read unrelated user files, access secrets, or send transcription data to external endpoints.
Install Mechanism
This is instruction-only in the registry, but the package includes a setup.sh that creates a venv and pip-installs faster-whisper and PyTorch (from the official PyTorch index URL). Installing packages via pip and downloading models is expected but does execute third-party code from PyPI/torch wheels; this is normal for Python tools but carries the usual supply-chain risk. The index URL used for CUDA wheels is the official download.pytorch.org host.
Credentials
No environment variables, credentials, or config paths are requested. The script only needs local binaries (python3, ffmpeg) and will install Python packages — proportionate to its function.
Persistence & Privilege
always is false and the skill does not request persistent or elevated platform privileges or modify other skills. It creates a local venv and writes its own files, which is normal for a setup script.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install faster-whisper-local - 安装完成后，直接呼叫该 Skill 的名称或使用
/faster-whisper-local触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release
元数据
常见问题
Faster Whisper Local 是什么？
Local speech-to-text using faster-whisper. High-performance transcription with GPU acceleration support. Includes word-level timestamps and distilled models.... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 973 次。
如何安装 Faster Whisper Local？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install faster-whisper-local」即可一键安装，无需额外配置。
Faster Whisper Local 是免费的吗？
是的，Faster Whisper Local 完全免费（开源免费），可自由下载、安装和使用。
Faster Whisper Local 支持哪些平台？
Faster Whisper Local 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Faster Whisper Local？
由 Damir Armanov（@damirikys）开发并维护，当前版本 v1.0.0。
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