299 citations · 303 across the 2 of their papers we have counts for
4 papers
Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model
Shaden Smith, Mostofa Patwary, Brandon Norick +17
Pretrained general-purpose language models can achieve state-of-the-art accuracies in various natural language processing domains by adapting to downstream tasks via zero-shot, few…
Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM
Deepak Narayanan, Mohammad Shoeybi, Jared Casper +9
Large language models have led to state-of-the-art accuracies across a range of tasks. However, training these models efficiently is challenging for two reasons: a) GPU memory capa…
Neural ODEs for Image Segmentation with Level Sets
Rafael Valle, Fitsum Reda, Mohammad Shoeybi +3
We propose a novel approach for image segmentation that combines Neural Ordinary Differential Equations (NODEs) and the Level Set method. Our approach parametrizes the evolution of…
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
Mohammad Shoeybi, Mostofa Patwary, Raul Puri +3
Recent work in language modeling demonstrates that training large transformer models advances the state of the art in Natural Language Processing applications. However, very large…