Click on the above “Beginner Learning Visuals” to select “Add Star” or “Pin” Heavyweight content delivered first-hand Source | AI Technology Review Translated by | bluemin Proofread by | Chen Caixian The Transformer architecture has become a popular research topic in the field of machine learning (especially in NLP), bringing us many important achievements, such … Read more
Originally from AI有道 Seven years ago, the paper “Attention is All You Need” introduced the transformer architecture, revolutionizing the entire field of deep learning. Today, all major models are based on the transformer architecture, yet the internal workings of the transformer remain a mystery. Last year, one of the authors of the transformer paper, Llion … Read more
Author: Chen Zhi Yan This article is approximately 3500 words long and is recommended for a 7-minute read. The Transformer is the first model that completely relies on the self-attention mechanism to compute its input and output representations. The mainstream sequence-to-sequence models are based on encoder-decoder recurrent or convolutional neural networks. The introduction of the … Read more
Source: AI Technology Online Today, I will share an article about the deep learning model Transformer. I would call it the best article explaining the Transformer model. The article mainly introduces the specific implementation of the Transformer model: Overall Architecture of Transformer Overview of Transformer Introduction to Tensors Self-Attention Mechanism Multi-Head Attention Mechanism Position-wise Feed-Forward … Read more
1 Algorithm Introduction The Transformer is a model that uses the attention mechanism to improve the training speed of the model. The Transformer can be said to be a deep learning model that is completely based on the self-attention mechanism, as it is suitable for parallel computation, and its inherent model complexity results in higher … Read more
Click on the above “Beginner Learning Visuals” to select “Star” or “Pin” Important content delivered promptly Author: Wang Bo Kings, Sophia Overview of the Content of This Article: Wang Bo Kings’ Recent Learning Notes on Transformer Recommended AI Doctor Notes Series Weekly Zhi Hua’s “Machine Learning” Handwritten Notes Officially Open Source! Printable version with PDF … Read more
Author: Wang Chen, Who Asks Questions@Zhihu (Authorized) Source: https://www.zhihu.com/question/362131975/answer/3058958207 Editor: Jishi Platform Why Summarize Transformers Through Eighteen Questions? There are two reasons: First, the Transformer is the fourth major feature extractor after MLP, RNN, and CNN, also known as the fourth foundational model; the recently popular chatGPT is also built on the Transformer, highlighting its … Read more
Transformer is a model that utilizes the attention mechanism to improve the training speed of models. For more information about the attention mechanism, you can refer to this article (https://zhuanlan.zhihu.com/p/52119092). The transformer can be said to be a deep learning model that is entirely based on the self-attention mechanism, as it is suitable for parallel … Read more
This article will cover theessence of Transformer, the principles of Transformer, and improvements in Transformer architecture in three aspects to help you understand Transformer. 1. Essence of Transformer Transformer Architecture: It mainly consists of four parts: input section (input-output embeddings and position encoding), multi-layer encoder, multi-layer decoder, and output section (output linear layer and Softmax). … Read more
5.17 The Intellectual The Intellectual Image Source: Pixabay Written by | Sun Ruichen Edited by | Li Shanshan ● ● ● Today, large language pre-trained neural network models such as ChatGPT have become widely known names. However, the algorithmic core behind GPT—the artificial neural network algorithm—has undergone an 80-year rollercoaster of ups and downs. During … Read more