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Faster Whisper Local
by
Damir Armanov
· GitHub ↗
· v1.0.0
973
Downloads
2
Stars
5
Active Installs
1
Versions
Install in OpenClaw
/install faster-whisper-local
Description
Local speech-to-text using faster-whisper. High-performance transcription with GPU acceleration support. Includes word-level timestamps and distilled models....
README (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.
Usage Guidance
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.
Capability Analysis
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`.
Capability Assessment
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install faster-whisper-local - After installation, invoke the skill by name or use
/faster-whisper-local - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release
Metadata
Frequently Asked Questions
What is Faster Whisper Local?
Local speech-to-text using faster-whisper. High-performance transcription with GPU acceleration support. Includes word-level timestamps and distilled models.... It is an AI Agent Skill for Claude Code / OpenClaw, with 973 downloads so far.
How do I install Faster Whisper Local?
Run "/install faster-whisper-local" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Faster Whisper Local free?
Yes, Faster Whisper Local is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Faster Whisper Local support?
Faster Whisper Local is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Faster Whisper Local?
It is built and maintained by Damir Armanov (@damirikys); the current version is v1.0.0.
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