OFFICE-Ai278/office-ai-GPT4-isizulu-xhosa-sesotho-llm

OFFICE Ai - Open Source Project is a 10-year initiative to build GPT-4 grade foundational language models for isiZulu, isiXhosa, and Sesotho. Includes data curation, slang integration, instruction tuning, and GGUF model releases. # office-ai-GPT4-isizulu-xhosa-sesotho-llm OFFICE Ai - Open Source Project is a 10-year initiative to build GPT-4 grade foundational language models for isiZulu, isiXhosa, and Sesotho. Includes data curation, slang integration, instruction tuning, and GGUF model releases. These models aim to preserve, empower, and modernize the use of these languages in AI-driven applications, bridging linguistic gaps and supporting digital inclusivity. The project targets foundational models at GPT-4-grade quality. Project Timeline & Approach Years 1–5: Data Curation & Preparation The first five years will focus on meticulously curating and refining diverse linguistic datasets critical for foundational model training. This includes gathering written and spoken corpora from peer-reviewed sources and everyday language use. First 11 Months of Each Year: Translation & Slang Factor Integration During the first 11 months of each year, extensive translation efforts will convert English and other language corpora into isiZulu, isiXhosa, and Sesotho. Special emphasis will be placed on incorporating contemporary slang and evolved colloquial expressions, reflecting the living nature of these languages. Month 12 of Each Year: Model Training & Deployment By the twelfth month, the curated datasets will be used to train the foundational models on cloud-based GPU infrastructure. The resulting models will be released in GGUF format for efficient deployment and broad compatibility. Years 5–10: Instruction Tuning & Refinement The latter five years will be dedicated to the instruct phase, where the foundational models undergo instruction tuning and fine-tuning to improve usability, safety, and alignment with user needs — enabling advanced natural language understanding and generation. Team & Funding We aim to employ 100 skilled linguists to lead translation, annotation, and validation. Funding will come from a combination of: Crowdsourced contributions Self-funding initiatives Donor grants …