With the rapid popularity of the Transformer model, Self-Attention and Multi-Head Attention have become core components in the field of Natural Language Processing (NLP).This article will analyze these two attention mechanisms from three aspects: brief introduction, workflow, and comparison. 1. Brief Introduction Self-Attention: Allows each element in the input sequence to focus on and weight … Read more
Machine Heart Release Author: Li Duo This work was mainly completed by me and Hu Jie, the author of SENet. I would also like to thank my two mentors at HKUST, Chen Qifeng and Zhang Tong, for their discussions and suggestions. This article introduces our paper accepted at CVPR 2021, Involution: Inverting the Inherence of … Read more
Abstract: Vision segmentation is a core task in the field of computer vision, aiming to classify pixels in images or video frames to partition them into different regions. Thanks to the rapid development of vision segmentation technology, it plays a critical role in various application areas such as autonomous driving, aerial remote sensing, and video … Read more
Follow the WeChat public account “ML_NLP” Set as “Starred” to receive heavy content promptly! Reprinted from | PaperWeekly ©PaperWeekly Original · Author｜Hai Chenwei School｜Master’s student at Tongji University Research Direction｜Natural Language Processing In the current NLP field, Transformer/BERT has become a fundamental application, and Self-Attention is the core part of both. Below, we attempt to … Read more
In the past two years, the BERT model has become very popular. Most people know about BERT but do not understand what it specifically is. In short, the emergence of BERT has completely changed the relationship between pre-training to generate word vectors and downstream specific NLP tasks, proposing the concept of training word vectors at … Read more
Click on the above “Beginner’s Guide to Vision“, choose to add “Star” or “Pin“ Important content delivered first This article is reproduced from Zhihu, with the author’s permission. https://zhuanlan.zhihu.com/p/146130215 Previously, I was looking at the self-attention in the DETR paper, and combined with the attention mechanism often mentioned in the lab meetings, I spent time … 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
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
Click on the above “Beginner’s Visual Learning” to select “Add to Favorites” or “Pin” Essential content delivered immediately Source: Python Data Science This article is about 7200 words long and is recommended to read in 14 minutes. In this article, we will explore the Transformer model and understand how it works. 1. Introduction Google’s BERT … Read more
Understanding Transformers Through Llama Model Architecture Llama Nuts and Bolts is an open-source project on GitHub that rewrites the inference process of the Llama 3.1 8B-Instruct model (80 billion parameters) from scratch using the Go language. The author is Adil Alper DALKIRAN from Turkey. If you are interested in how LLMs (Large Language Models) and … Read more