Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment

no code implementations • 6 May 2024 • Abhinav Agarwalla, Abhay Gupta, Alexandre Marques, Shubhra Pandit, Michael Goin, Eldar Kurtic, Kevin Leong, Tuan Nguyen, Mahmoud Salem, Dan Alistarh, Sean Lie, Mark Kurtz

We achieve this for the LLaMA-2 7B model by combining the SparseGPT one-shot pruning method and sparse pretraining of those models on a subset of the SlimPajama dataset mixed with a Python subset of The Stack dataset.

Arithmetic Reasoning Code Generation +2