whisper Skill
OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR Published by NousResearch in hermes-agent.
What is whisper Skill?
OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Deployment
- Design and media
- Deployment use cases
- Design and media use cases
Technical details
- Install or run with Copy skill directory
When to use whisper Skill
- Use it for deployment.
- Use it for design and media.
Built with
Editorial notes
Source
- Creator: NousResearch
- Repository: NousResearch/hermes-agent
- Skill file: optional-skills/mlops/whisper/SKILL.md
What it does
OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR
Skill instructions
Whisper - Robust Speech Recognition OpenAI's multilingual speech recognition model. When to use Whisper Use when: - Speech-to-text transcription (99 languages) - Podcast/video transcription - Meeting notes automation - Translation to English - Noisy audio transcription - Multilingual audio processing Metrics: - 72,900+ GitHub stars - 99 languages supported - Trained on 680,000 hours of audio - MIT License Use alternatives instead: - AssemblyAI: Managed API, speaker diarization - Deepgram: Real-time streaming ASR - Google Speech-to-Text: Cloud-based Quick start Installation bash Requires Python 3.8-3.11 pip install -U openai-whisper Requires ffmpeg macOS: brew install ffmpeg Ubuntu: sudo apt install ffmpeg Windows: choco install ffmpeg Basic transcription python import whisper Load model model = whisper.loadmodel("base") Transcribe result = model.transcribe("audio.mp3") Print text print(result["text"]) Access segments for segment in result["segments"]: print(f"[{segment['start']:.2f}s -
Explore related resources
Frequently asked questions
What is whisper?
whisper is a open-source AI agent skill with Copy skill directory. OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params).
Who is whisper best for?
whisper is best for reusing agent instructions, scripts, and references, deployment workflows, design and media workflows.
How do I install whisper?
Install or run whisper using Copy skill directory. Check whisper for the latest setup command.
Is whisper actively maintained?
whisper may need a closer maintenance check before production use.
Auto-fetched from GitHub.
