Achieving Better Results and Efficiency in Language Model Fine-Tuning

Yanli Liu

Towards Data Science

Fine-tuning is one of the most popular techniques for adapting language models to specific tasks.

However, in most cases, this will require large amounts of computing power and resources.

Recent advances, among them PeFT, the parameter-efficient fine-tuning such as the Low-Rank Adaptation method, Representation Fine-Tuning, and ORPO



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