Enhance Cost Efficiency in Domain Adaptation with PruneMe 

Speaker: Shamane Siri, Ph.D. , Head of Applied NLP Research, Arcee.ai
Our PruneMe repository, inspired by "The Unreasonable Ineffectiveness of the Deeper Layers," demonstrates a layer pruning technique for Large Language Models (LLMs) that enhances cost efficiency in domain adaptation. By removing redundant layers, we facilitate continual pre-training on streamlined models. Subsequently, these models can be merged into a top-performing general model using advanced techniques like Evolve Merging, offering a cost-effective approach to model optimization and adaptation.