Leveraging Large Language Models for Improving Agricultural Extension in Nigeria
Keywords: NLP, Agriculture Extension, Farmers, Nigeria, AI-driven Platform, Large Language Models, Virtual Agricultural Extension Agent, Fine-tuning, GPT-3.5, Context-specific Information
TL;DR: Leveraging LLMs for Improving Agricultural Extension in Nigeria
Abstract: Access to accurate and timely agricultural information and agriculture extension experts is essential for farmers to make informed decisions and improve their agricultural practices. However, farmers in Nigeria, especially those in rural areas, face significant challenges in accessing such information and expertise. This research addresses the information gap by leveraging the power of large language models (LLMs) to develop an AI-driven platform that serves as agricultural extension services in Nigeria. Specifically, we fine-tuned OpenAI's GPT-3.5 model, an advanced LLM, to develop a virtual agricultural extension agent that can provide Nigeria agriculture context-specific information to farmers.
Submission Category: Machine learning algorithms
Submission Number: 4
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