YORI-LLaMA-Quantized

YORI-LLaMA-Quantized is a Yoruba large language model specialized in text generation and AI-based assistance in Yoruba. It was quantized from its base model , Jacaranda/yorubaLLaMA, to achieve lighter memory usage and faster inference while maintaining strong linguistic performance.

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💬 Description

YORI-LLaMA-Quantized is trained to generate and understand natural Yoruba text with contextual fluency and syntactic awareness. It can be used for:

• Yoruba AI assistants
• fine-tuned for Chatbot
• Text completion, storytelling, and creative generation
• Language preservation and computational linguistics research

⚠️ Limitations

• Code-switching weakness: The model struggles when Yoruba and English are mixed, leading to misinterpretations or incorrect tokens.
• Numerical inaccuracies: Occasionally produces factual errors, e.g., reporting mẹ́ẹ̀dógún (15) instead of mẹ́rìndínlógójì (36) for the number of Nigerian states.
• Ambiguous prompts: May output irrelevant or nonsensical responses when the query lacks clarity.

These limitations suggest the need for more diverse and updated training data across dialects and domains.

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⚙️ Inference Notice

A key consideration when running inference is model precision. YORI was quantized for efficiency, but inference should be performed in FP16 precision for stability and performance.

Example snippet:

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🧩 Intended Use

This model is intended for:

• Academic and research purposes
• Educational AI assistants
• Yoruba language technology development

Do not use this model for:

• Disinformation or impersonation
• Generating offensive or harmful content
• Applications violating user consent or privacy

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