Data Science, AI, Llm, Generalization.
makes this process 900 times faster, which is crucial when dealing with massive datasets. “To achieve this result, we developed SubLoRA, a simple low-dimensional nonlinear parameterization that leads to non-vacuous generalization bounds for very large models with up to 849 million parameters,”