Identify sentiment and filter Arabic text across five dialects offline.
npx skills add https://github.com/Moshe-ship/mkhlab --skill sarih
Please help me install this Agent Skill. Skill: sarih Source: https://github.com/Moshe-ship/mkhlab/tree/main/hermes-skills/sarih Command: npx skills add https://github.com/Moshe-ship/mkhlab --skill sarih
Arabic content moderation and sentiment detection across five dialects, designed to operate offline.
Run sarih on your dataset to filter out harmful text.
High-intent search queries and answers about installing and using this skill.
Arabic sentiment analysis can run offline across five dialects using a lightweight NLP classifier that processes text without internet connectivity. This enables local moderation of social media comments and user-generated content safely.
Yes, offline content moderation supports Gulf and Egyptian dialects alongside Levantine, Maghrebi, and Iraqi. A lightweight NLP classifier filters harmful text locally without relying on external API calls or internet access.
Offline content filtering and sentiment detection support five Arabic dialects: Egyptian, Gulf, Levantine, Maghrebi, and Iraqi. This allows platforms to identify toxic content and filter user feedback across regional variations.
Yes, offline Arabic NLP classification works for moderating customer feedback by identifying sentiment and filtering inappropriate content. It processes local text datasets across five dialects using a lightweight classifier without internet dependency.
You can filter toxic Arabic content on mixed dialect platforms by running offline sentiment analysis across Egyptian, Gulf, Levantine, Maghrebi, and Iraqi text. The lightweight NLP classifier flags harmful content locally.
PatkikExtract sentiment, topics, keywords, and insights from text content.
brainbrewlabsCompile contextual evidence and policy-aligned decision options for flagged content review.
Moshe-shipDetect Arabic dialects and map input to Egyptian, Gulf, Levantine, Maghrebi, Iraqi, or MSA.
jackquelinunpredictable827Detect sentiment and toxicity scores in Arabic text across five dialects.
