SIBO : A simple booster for parameter-efficient fine-tuning
Fine-tuning all parameters of large language models (LLMs) necessitates substantial computational power and extended time. Latest advancements in parameter-efficient fine-tuning (PEFT) techniques, such as Adapter tuning and LoRA, allow for adjustments to only a minor fraction of the parameters of th...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2024
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/9624 https://ink.library.smu.edu.sg/context/sis_research/article/10624/viewcontent/ACL24Findings_SIBO__1_.pdf |
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| Institution: | Singapore Management University |
| Language: | English |