laser
Layer-Selective Rank Reduction (LASER) enhances performance in language models by employing low-rank approximations of weight matrices. This technique optimizes reasoning tasks such as question-answering without further training by targeting specific layers and parameters. The project is under active development, focusing on refactoring for better flexibility and usability. It provides reproducible results across various models and benchmarks while encouraging community contributions and interaction. Core features include efficient hyperparameter tuning and adaptability for different language models.