en
AI Ranking
每月不到10元,就可以无限制地访问最好的AIbase。立即成为会员
Home
News
Daily Brief
Income Guide
Tutorial
Tools Directory
Product Library
en
AI Ranking
Search AI Products and News
Explore worldwide AI information, discover new AI opportunities
AI News
AI Tools
AI Cases
AI Tutorial
Type :
AI News
AI Tools
AI Cases
AI Tutorial
2024-09-16 15:03:28
.
AIbase
.
11.8k
New Fine-Tuning Framework LoRA-Dash: Efficiently Addressing Specific Tasks with Significantly Reduced Computational Requirements
Recently, a research team from Shanghai Jiao Tong University and Harvard University introduced a novel model fine-tuning method — LoRA-Dash. This new approach claims to be more efficient than existing LoRA methods, particularly in the fine-tuning of specific tasks, achieving the same results with an 8 to 16 times reduction in the number of parameters. This is undoubtedly a major breakthrough for fine-tuning tasks that require substantial computational resources. In the context of the rapid development of large-scale language models, the demand for fine-tuning specific tasks is steadily increasing. However, fine-tuning often