Software Engineering Meets Web Development With LoRA Land
LoRA Land: 310 fine-tuned LLMs rival GPT-4 performance with fewer params & lower memory usage, making large language models more practical in real-world applications.
This is a Plain English Papers summary of a research paper called LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview Low Rank Adaptation (LoRA) is a method for efficiently fine-tuning large language models (LLMs) with fewer trainable parameters and lower memory usage. This paper aims to assess the viability of training and deploying LoRA-fine-tuned LLMs in real-world applications. The researchers evaluate the performance of LoRA-fine-tuned model...