Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Transcribe audio to text with Whisper models via inference.sh CLI. Models: Fast Whisper Large V3, Whisper V3 Large. Capabilities: transcription, translation,...
Transcribe audio to text with Whisper models via inference.sh CLI. Models: Fast Whisper Large V3, Whisper V3 Large. Capabilities: transcription, translation,...
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Transcribe audio to text via inference.sh CLI.
curl -fsSL https://cli.inference.sh | sh && infsh login infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://audio.mp3"}' Install note: The install script only detects your OS/architecture, downloads the matching binary from dist.inference.sh, and verifies its SHA-256 checksum. No elevated permissions or background processes. Manual install & verification available.
ModelApp IDBest ForFast Whisper V3infsh/fast-whisper-large-v3Fast transcriptionWhisper V3 Largeinfsh/whisper-v3-largeHighest accuracy
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://meeting.mp3"}'
infsh app sample infsh/fast-whisper-large-v3 --save input.json # { # "audio_url": "https://podcast.mp3", # "timestamps": true # } infsh app run infsh/fast-whisper-large-v3 --input input.json
infsh app run infsh/whisper-v3-large --input '{ "audio_url": "https://french-audio.mp3", "task": "translate" }'
# Extract audio from video first infsh app run infsh/video-audio-extractor --input '{"video_url": "https://video.mp4"}' > audio.json # Transcribe the extracted audio infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "<audio-url>"}'
# 1. Transcribe video audio infsh app run infsh/fast-whisper-large-v3 --input '{ "audio_url": "https://video.mp4", "timestamps": true }' > transcript.json # 2. Use transcript for captions infsh app run infsh/caption-videos --input '{ "video_url": "https://video.mp4", "captions": "<transcript-from-step-1>" }'
Whisper supports 99+ languages including: English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, Hindi, Russian, and many more.
Meetings: Transcribe recordings Podcasts: Generate transcripts Subtitles: Create captions for videos Voice Notes: Convert to searchable text Interviews: Transcription for research Accessibility: Make audio content accessible
Returns JSON with: text: Full transcription segments: Timestamped segments (if requested) language: Detected language
# Full platform skill (all 150+ apps) npx skills add inference-sh/skills@inference-sh # Text-to-speech (reverse direction) npx skills add inference-sh/skills@text-to-speech # Video generation (add captions) npx skills add inference-sh/skills@ai-video-generation # AI avatars (lipsync with transcripts) npx skills add inference-sh/skills@ai-avatar-video Browse all audio apps: infsh app list --category audio
Running Apps - How to run apps via CLI Audio Transcription Example - Complete transcription guide Apps Overview - Understanding the app ecosystem
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.