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Generative AI with LLMs: PEFT Methods: How to Fine-Tune Large Language Models with Less Memory

Learn what PEFT methods are and how they can help you fine-tune large language models (LLMs) with minimal memory and maximal performance.


“PEFT methods can reduce the memory needed for fine-tuning dramatically, sometimes to just 12-20% of the memory needed for full fine-tuning.” Is this true or false?

A. True
B. False


A. True


The correct answer is A. True. PEFT methods can reduce the memory needed for fine-tuning dramatically, sometimes to just 12-20% of the memory needed for full fine-tuning. PEFT stands for Parameter-Efficient Fine-Tuning, and it is a class of techniques that enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model’s parameters. PEFT methods only fine-tune a small number of (extra) model parameters, such as adapters, prefixes, or soft prompts, that are inserted into the original model layers. This reduces the computational and storage costs of fine-tuning, as well as the risk of overfitting or catastrophic forgetting. According to a recent empirical analysis, PEFT methods can achieve comparable performance to full fine-tuning while using much less memory and time. For example, LoRA, a low-rank adaptation method, can reduce the memory consumption to 12% of full fine-tuning, and Prefix Tuning, a continuous prompt optimization method, can reduce it to 20%.

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Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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