Interpretation: AI Generates the Future This article introduces the Multimodal Large Language Model (MLLM), its definition, applications using challenging prompts, and the top models that are reshaping computer vision. Table of Contents What is a Multimodal Large Language Model (MLLM)? Applications and Cases of MLLMs in Computer Vision Leading Multimodal Large Language Models Future Outlook … Read more
This article is adapted from: Foreign Languages, 2024, Issue 4 Citation: Yuan Yulin. Language Processing Mechanism and Theoretical Implications of Large Models like ChatGPT[J]. Foreign Languages, 2024, 47(4): 2-14. Introduction: Understanding the Source of Large Models’ Language Proficiency As many may know, modern large language models (LLMs) like ChatGPT possess powerful capabilities in language understanding … Read more
When handling long sequences, Transformers face challenges such as attention dispersion and increased noise. As the sequence length increases, each token must compete for attention scores with more tokens, which can lead to diluted attention scores. This dilution can result in less concentrated and relevant contextual representations, particularly affecting tokens that are far apart from … Read more
Perhaps the breakthrough in computer vision and machine learning over the past decade is the invention of GANs (Generative Adversarial Networks) — a method that introduced the possibility of going beyond the content that already exists in the data, serving as a stepping stone into a whole new field now known as generative modeling. However, … Read more
Zhou Bowen, Director and Chief Scientist of Shanghai Artificial Intelligence Laboratory, Tsinghua University Huaiyan Chair Professor, and Tenured Professor of the Department of Electronic Engineering, IEEE/CAAI Fellow, member of the National New Generation Artificial Intelligence Governance Professional Committee, and expert committee member of the New Generation Artificial Intelligence Development Research Center, Chief Scientist of the … Read more
Source: Machine Heart Transformers have recently become the new dominators in the visual field. What specific applications does this model architecture from the NLP field have in the CV field? As an attention-based encoder-decoder architecture, Transformers have not only revolutionized the field of Natural Language Processing (NLP) but also made some pioneering contributions in the … Read more
Source: Machine Learning Beginners This article is about 4500 words long and is recommended to be read in 8 minutes. We will explore the BERT model and understand how it works, which is a very important part of NLP (Natural Language Processing). Introduction Since Google announced BERT’s outstanding performance in 11 NLP tasks at the … Read more
Hello everyone! I’m back! Today we are going to talk about a super hot topic – how to build your own chat system using HuggingChat. This tool provides us with a “building blocks” platform, allowing us to easily create chatbots similar to ChatGPT. Alright, let’s begin today’s Python journey! What is HuggingChat? HuggingChat is a … Read more
Follow the WeChat public account “ML_NLP“ Set as “starred” for heavy content delivery! Author | Adherer Organizer | NewBeeNLP Interview tips knowledge compilation series, continuously updated Full of valuable content, recommended to collect, or as usual, see you in the background (code: BT) 1. What Is the Basic Principle of BERT? BERT comes from Google’s … Read more
Introduction Happy Spring Festival everyone! Recently, DeepSeek has gained a lot of popularity. Today, I will share a program that uses Streamlit to deploy the DeepSeek-R1-Distill-Qwen-7B model. By deploying it locally, you can easily utilize DeepSeek’s conversational capabilities. Relationship with Qwen DeepSeek-R1-Distill-Qwen-7B is an open-source inference model based on the Qwen-7B architecture, distilled from the … Read more