القائمة
Local speech-to-text with MLX Whisper (Apple Silicon optimized, no API key).
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/duclm1x1/Dive-Ai --skill mlx-whisperيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
عرض SKILL.md
استنادا إلى تصنيف SOC المهني
| name | mlx-whisper |
| version | 1.0.0 |
| description | Local speech-to-text with MLX Whisper (Apple Silicon optimized, no API key). |
| homepage | https://github.com/ml-explore/mlx-examples/tree/main/whisper |
| metadata | {"clawdbot":{"emoji":"🍎","requires":{"bins":["mlx_whisper"]},"install":[{"id":"pip","kind":"pip","package":"mlx-whisper","bins":["mlx_whisper"],"label":"Install mlx-whisper (pip)"}]}} |
Local speech-to-text using Apple MLX, optimized for Apple Silicon Macs.
mlx_whisper /path/to/audio.mp3 --model mlx-community/whisper-large-v3-turbo
# Transcribe to text file
mlx_whisper audio.m4a -f txt -o ./output
# Transcribe with language hint
mlx_whisper audio.mp3 --language en --model mlx-community/whisper-large-v3-turbo
# Generate subtitles (SRT)
mlx_whisper video.mp4 -f srt -o ./subs
# Translate to English
mlx_whisper foreign.mp3 --task translate
| Model | Size | Speed | Quality |
|---|---|---|---|
| mlx-community/whisper-tiny | ~75MB | Fastest | Basic |
| mlx-community/whisper-base | ~140MB | Fast | Good |
| mlx-community/whisper-small | ~470MB | Medium | Better |
| mlx-community/whisper-medium | ~1.5GB | Slower | Great |
| mlx-community/whisper-large-v3 | ~3GB | Slowest | Best |
| mlx-community/whisper-large-v3-turbo | ~1.6GB | Fast | Excellent (Recommended) |
~/.cache/huggingface/mlx-community/whisper-tiny; use --model mlx-community/whisper-large-v3-turbo for best results