Optimizing LLMs From a Dataset Perspective

This article focuses on improving the modeling performance of LLMs by finetuning them using carefully curated datasets. Specifically, this article highlights strategies that involve modifying, utilizing, or manipulating the datasets for instruction-based finetuning rather than altering the model architecture or training algorithms (the latter will be topics of a future article). This article will also explain how you can prepare your own datasets to finetune open-source LLMs.