LLM-as-Judge - Instruction Finetuning and Supervised Fine-Tuning

Learn about using large language models as evaluation judges and explore instruction fine-tuning techniques through this comprehensive lecture that covers the methodology of leveraging LLMs to assess model outputs, understand the principles behind supervised fine-tuning (SFT) for instruction-following capabilities, and examine practical applications of these approaches in improving model performance and alignment with human preferences.