Fine-tuning language models for specific tasks is a popular technique that often requires significant computing power and resources. Recent advances, such as PeFT (parameter-efficient fine-tuning), offer more efficient methods like Low-Rank Adaptation, Representation Fine-Tuning, and ORPO. These advancements aim to improve results and efficiency in language model fine-tuning.
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Source link: https://towardsdatascience.com/combining-orpo-and-representation-fine-tuning-for-efficient-llama3-alignment-77f6a2e3af8c
#EfficientAlignment: Combining ORPO and Fine-Tuning for LLAMA3 #Representation
![Combining ORPO and Representation Fine-Tuning for Efficient LLAMA3 Alignment | by Yanli Liu | Jun, 2024](https://i0.wp.com/webappia.com/wp-content/uploads/2024/06/1a7IIGPq8nRF6WXLoZ2rNOw@2x.jpeg?fit=758%2C405&quality=89&ssl=1)
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