4 citations · 6 across the 4 of their papers we have counts for
3 papers · 1 filter
Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment
Abhinav Agarwalla, Abhay Gupta, Alexandre Marques +9
Large language models (LLMs) have revolutionized Natural Language Processing (NLP), but their size creates computational bottlenecks. We introduce a novel approach to create accura…
Sparse Fine-tuning for Inference Acceleration of Large Language Models
Eldar Kurtic, Denis Kuznedelev, Elias Frantar +2
We consider the problem of accurate sparse fine-tuning of large language models (LLMs), that is, fine-tuning pretrained LLMs on specialized tasks, while inducing sparsity in their…
The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models
Eldar Kurtic, Daniel Campos, Tuan Nguyen +5
Transformer-based language models have become a key building block for natural language processing. While these models are extremely accurate, they can be too large and computation…