What makes Faster Whisper Local notable?

1.8K downloads. Trust evidence available

How should Faster Whisper Local be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Faster Whisper Local

Local speech-to-text using faster-whisper. High-performance transcription with GPU acceleration support. Includes word-level timestamps and distilled models.... Skill: Faster Whisper Local Owner: jeminay Summary: Local speech-to-text using faster-whisper. High-performance transcription with GPU acceleration support. Includes word-level timestamps and distilled models.... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-02-20T06:04:43.270Z | user Initial release Archive index: Archive v1.0.0: 6 files, 6590 bytes Files: requirements.txt (117b), scripts/transcribe.py (6292b),

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.8k

Updated

Oct 10, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.8K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.8K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.0release · observed Feb 20, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: medium.

clawhub skill install s170dx4nw2adr8scv090bb28dd84pbe2:faster-whisper-local

Python environment detected. Create a strict virtual environment (`python -m venv .venv`) before installing dependencies to prevent system-level package conflicts.
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-jeminay-faster-whisper-local/snapshot"

Documentation

CLAWHUB

4,301 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

---
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.

```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`.

_meta.json

{
  "ownerId": "kn73589k2rv646tm107cp6d90s81g7xy",
  "slug": "faster-whisper-local",
  "version": "1.0.0",
  "publishedAt": 1771567483270
}

skill-card.md

## Description:

Local speech-to-text using faster-whisper with GPU acceleration support, word-level timestamps, and distilled model options.

This skill is ready for commercial/non-commercial use.

## Publisher:

[jeminay](https://clawhub.ai/user/jeminay)

### License/Terms of Use:


## Use Case:

Developers and agents use this skill to transcribe local audio files into plain text or JSON, with optional model selection, language selection, word timestamps, and voice activity detection.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Setup downloads current Python packages and Whisper model assets into a local virtual environment.

Mitigation: Install in a controlled environment and pin and hash dependencies before setup when higher assurance is required.

Risk: Local audio transcription may process sensitive audio content.

Mitigation: Review local data handling requirements before processing audio files and keep generated transcripts within the approved environment.

## Reference(s):


## Skill Output:

**Output Type(s):** [Text, JSON, Shell commands, Configuration]

**Output Format:** [Plain text transcript or JSON transcript metadata, with shell commands and configuration guidance for setup and execution.]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Can write transcript output to a local file when requested.]

## Skill Version(s):

1.0.0 (source: server release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

requirements.txt

# Core dependency — PyTorch installed separately by setup script (with CUDA if GPU detected)
faster-whisper>=1.0.0

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