Practical Low Rank Decomposition for Large Language Models The huge number of parameters in modern Large Language Models makes them hard to deploy as they require a lot of memory and compute resources. Many solutions for reducing the number of […]
Episode XXIII
Dense Retrieval for Allegro Search Engine Modern system designs for e-commerce search are complex, multi-layered systems that must adhere to various online and offline performance requirements. Retrieval is a key component of search engines. In the face of today’s dominance […]
Practical Low Rank Decomposition for Large Language Models The huge number of parameters in modern Large Language Models makes them hard to deploy as they require a lot of memory and compute resources. Many solutions for reducing the number of […]
Scaling Laws for Fine-Grained Mixture of Experts Mixture of Experts (MoE) models have emerged as a primary solution for reducing the computational cost of Large Language Models. In this work, we analyze their scaling properties, incorporating an expanded range of […]