作者将这种策略称为混合深度(Mixture-of-Depths,MoD)。 作者还提到,MoD技术还允许在性能和速度之间进行权衡。一方面,可以训练一个MoD transformer在最终的对数概率训练目标上比普通transformer提高1.5%,并且训练所需的挂钟时间(wall-clock time)相当。另一方面,可以将一个MoD transformer训练达到与isoFLOP最佳的传统...
《Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping》阅读笔记 窥探 nlp算法工程师5 人赞同了该文章 背景 基于transformer架构的预训练语言模型展现出了明显的优越性,刷新了众多nlp下游任务的效果。但是预训练语言模型是从海量无监督数据集中学习知识,且模型规模一般都比较大(base...
The surge of pre-trained language models has begun a new era in the field of Natural Language Processing (NLP) by allowing us to build powerful language models. Among these models, Transformer-based models such as BERT have become increasingly popular due to their state-of-the-art performance...
1. Language Model 语言模型来辅助NLP任务已经得到了学术界较为广泛的探讨,通常有两种方式: 1.1 Feature-based方法 Feature-based指利用语言模型的中间结果也就是LM embedding, 将其作为额外的特征,引入到原任务的模型中,例如在下图中,采用了两个单向RNN构成的语言模型,将语言模型的中间结果 引入到序列标注模型中,如...
language model. The simple goal of the GPT-2 language model, a sizable transformer-based language model trained on 40GB of internet text, is to predict the next word given all the terms in a sequence. The synthetic text samples produced by GPT-2 are cohesive continuations of the input and...
1. 语言模型 (Language Model) 大模型-大的语言模型,学习大模型之前必须了解什么是语言模型 语言模型可视为一个函数,输入是一个句子,输出是一个分数,此分数是评估所输入的句子是人说的话的概率 判断是不是句子,基于当前的词预测下一个词 语言模型本身是统计模型 probability of a sentence ...
Jacob Devlin等发布的《BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding》,BERT(Bidirectional Encoder Representations from Transformers)是一种预训练语言表示的方法,它通过在大量文本上进行预训练,学习到深层次的双向语言表示。BERT的关键创新在于它的双向训练策略,这使得模型能够同时考虑...
In recent years, methods using large-scale pre-trained language models (PLMs), in particular the widely used transformer-based PLMs, have become a new paradigm of NLG, allowing generation of more diverse and fluent text. However, due to the lower level of interpretability of deep neural ...
Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0). - jalammar/ecco
powerful transformer developed by the Applied Deep Learning Research team at NVIDIA. This repository is for ongoing research on training large transformer language models at scale. We developed efficient, model-parallel (tensor and pipeline), and multi-node pre-training of transformer based models such...