This article discusses the creation of a Verifier-Guided Retrieval-Augmented Generation (RAG) and Supervised Language Model (SLM) learning loop. It details the use of QLoRA for efficient fine-tuning and introduces Jev as a component within this system. The core concept revolves around the challenge of verifying the outputs of AI models, particularly in complex learning loops. AI
IMPACT This approach could improve the reliability and accuracy of AI models by establishing a robust verification process within their learning cycles.
RANK_REASON The item describes a technical approach to building an AI learning loop, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]
Read on Medium — fine-tuning tag →
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