MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Owing to its robust performance and broad applicability when compared to other methods, LoRA or Low-Rank Adaption is one of the most popular PEFT or Parameter Efficient Fine-Tuning methods for fine-tuning a large language model. The LoRA framework employs two low-rank matrices to decompose, and approximate the updated weights in the FFT or Full Fine […]

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artificial intelligence fft fine-tuning fine tuning llm framework gpt-4 language language model large language large language model lora low mora peft performance popular robust supervised fine-tuning