LoRA+MoE: A Historical Interpretation of the Combination of Low-Rank Matrices and Multi-Task Learning

LoRA+MoE: A Historical Interpretation of the Combination of Low-Rank Matrices and Multi-Task Learning

↑↑↑ Follow and Star Kaggle Competition Guide Kaggle Competition Guide Author: Elvin Loves to Ask, excerpted from Zhai Ma LoRA+MoE: A Historical Interpretation of the Combination of Low-Rank Matrices and Multi-Task Learning This article introduces some works that combine LoRA and MoE, hoping to be helpful to everyone. 1. MoV and MoLoRA Paper: 2023 | … Read more

How Much Parameter Redundancy Exists in LoRA? New Research: Cutting 95% Can Still Maintain High Performance

How Much Parameter Redundancy Exists in LoRA? New Research: Cutting 95% Can Still Maintain High Performance

MLNLPThe MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP graduate students, university professors, and corporate researchers.The vision of the communityis to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners.Source | Machine HeartEditor | … Read more

How Much Parameter Redundancy Exists in LoRA? New Research: Cutting 95% Can Maintain High Performance

How Much Parameter Redundancy Exists in LoRA? New Research: Cutting 95% Can Maintain High Performance

Reported by Machine Heart Editor: Zhang Qian How much parameter redundancy exists in LoRA? This innovative research introduces the LoRI technology, which demonstrates that even significantly reducing the trainable parameters of LoRA can still maintain strong model performance. The research team tested LoRI on mathematical reasoning, code generation, safety alignment, and eight natural language understanding … Read more