Fine-Tuning Large Language Models With Tailored Synthetic Data
CodecLM: Aligning LLMs with tailored synthetic data boosts performance & capabilities on specific tasks/domains by fine-tuning on custom-generated training data.
This is a Plain English Papers summary of a research paper called CodecLM: Aligning Language Models with Tailored Synthetic Data. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview This paper introduces CodecLM, a novel approach to aligning large language models (LLMs) with tailored synthetic data. The goal is to improve the performance and capabilities of LLMs on specific tasks or domains by fine-tuning them on custom-generated training data. The authors propose a framework for creating this synthetic data using...