2.2k citations · 3.4k across the 5 of their papers we have counts for
7 papers
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Reducing Activation Recomputation in Large Transformer Models
Vijay Korthikanti, Jared Casper, Sangkug Lym +4
Training large transformer models is one of the most important computational challenges of modern AI. In this paper, we show how to significantly accelerate training of large trans…
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…
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…
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
Dario Amodei, Rishita Anubhai, Eric Battenberg +31
We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages. Because it replaces entire pip…
Deep Speech: Scaling up end-to-end speech recognition
Awni Hannun, Carl Case, Jared Casper +8
We present a state-of-the-art speech recognition system developed using end-to-end deep learning. Our architecture is significantly simpler than traditional speech systems, which r…