examples of data labelling, translation quality evaluation and prompt engineering for Swahili AI dataset
# Swahili-ai-data
welcome!This repiratory showcase my cababilities in data annotation,linguistic quality assurance and RLHF( Reinforcement Learning from HumanFeedback) prompt evaluation for swahili Large Language Models (LLMs).
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## COre capabilities
* **Data annotation& Tagging :*structuring unstructuring swahili text for classification models.
* **Linguistic QA:*identifying subtlegrammatical, contextual, and cultural translation issues.
* **Prompt Engineering & Evaluation:*Assessing LLM outputs for safety,helpuflness, and localization accuracy.
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## 1.Text classification& Intent Tagging
* ** Objective:**Categorizing user queries to train conversational AI assistants.
* **sample Data:**
|User Query(swahili)|Primary Intent|Sub Category Intent|Language Quality Notes|
|:---|:---|:---|:---|
|"Ninasanduku gani la malipo na nawezaje kutoa pesa kwa m-pesa?"|Financial_Inquiry|withdrawal_method|standard colloquial syntax,includes regional terminology(M-pesa).|programu hii haifanyi kazi."|Technical_support|App_cash|High Agency tone;|