LLM in a flash: Efficient Large Language Model Inference with Limited Memory

no code implementations • 12 Dec 2023 • Keivan Alizadeh, Iman Mirzadeh, Dmitry Belenko, Karen Khatamifard, Minsik Cho, Carlo C Del Mundo, Mohammad Rastegari, Mehrdad Farajtabar

These methods collectively enable running models up to twice the size of the available DRAM, with a 4-5x and 20-25x increase in inference speed compared to naive loading approaches in CPU and GPU, respectively.

Language Modelling Large Language Model +1

ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models

1 code implementation • 6 Oct 2023 • Iman Mirzadeh, Keivan Alizadeh, Sachin Mehta, Carlo C Del Mundo, Oncel Tuzel, Golnoosh Samei, Mohammad Rastegari, Mehrdad Farajtabar

Large Language Models (LLMs) with billions of parameters have drastically transformed AI applications.

Recurrent Poisson Factorization for Temporal Recommendation

1 code implementation • 4 Mar 2017 • Seyed Abbas Hosseini, Keivan Alizadeh, Ali Khodadadi, Ali Arabzadeh, Mehrdad Farajtabar, Hongyuan Zha, Hamid R. Rabiee

Poisson factorization is a probabilistic model of users and items for recommendation systems, where the so-called implicit consumer data is modeled by a factorized Poisson distribution.

Recommendation Systems