MJ Windows Faster Whisper
by @magejosh
Local speech-to-text with the faster-whisper backend (CTranslate2). Use when transcribing audio locally, setting up the faster-whisper model cache, or replac...
clawhub install mj-windows-faster-whisperπ About This Skill
name: faster-whisper description: Local speech-to-text with the faster-whisper backend (CTranslate2). Use when transcribing audio locally, setting up the faster-whisper model cache, or replacing a whisper-cli workflow with a faster local engine.
Faster Whisper
Overview
Use faster-whisper for local transcription with low latency and a reusable model cache.
Rules
ggml models work here; faster-whisper uses CTranslate2 model folders.device='cpu' and compute_type='int8' unless the machine is explicitly configured for GPU.Setup
1. Confirm python and ffmpeg are available.
2. Install the Python packages needed for local inference:
- faster-whisper
- ctranslate2
- huggingface_hub
3. Use the project repo https://github.com/SYSTRAN/faster-whisper for install/setup guidance.
4. Download Systran/faster-whisper-small from https://huggingface.co/Systran/faster-whisper-small into a stable local folder such as:
- C:\Users\joshu\.openclaw\tools\faster-whisper\models\Systran-faster-whisper-small
4. Reuse that folder for repeat runs.
5. If the user only has a ggml-*.bin file, explain that it belongs to whisper.cpp and is not usable here.
Transcription
1. Convert Telegram OGG/Opus audio to WAV if needed. 2. Load the local model folder. 3. Transcribe and return the plain-text result.
βοΈ Configuration
1. Confirm python and ffmpeg are available.
2. Install the Python packages needed for local inference:
- faster-whisper
- ctranslate2
- huggingface_hub
3. Use the project repo https://github.com/SYSTRAN/faster-whisper for install/setup guidance.
4. Download Systran/faster-whisper-small from https://huggingface.co/Systran/faster-whisper-small into a stable local folder such as:
- C:\Users\joshu\.openclaw\tools\faster-whisper\models\Systran-faster-whisper-small
4. Reuse that folder for repeat runs.
5. If the user only has a ggml-*.bin file, explain that it belongs to whisper.cpp and is not usable here.
π Constraints
ggml models work here; faster-whisper uses CTranslate2 model folders.device='cpu' and compute_type='int8' unless the machine is explicitly configured for GPU.