Build Large Language Models from Scratch: A Hands-On Guide to GPT Architecture Implementation
1 months ago 高效码农Building Large Language Models From Scratch: A Hands-On Journey Through GPT Architecture Introduction Have you ever wondered how ChatGPT and similar AI systems actually work under the hood? While most tutorials teach you to use existing APIs, “Build a Large Language Model (From Scratch)” takes a radically different approach. This comprehensive guide walks you through creating a GPT-like language model line-by-line, giving you fundamental insights that pre-packaged solutions can’t provide. Based on the official repository for Sebastian Raschka’s book, this article explores how anyone can understand LLM mechanics by building them from the ground up. What You’ll Actually Build Through …
Inside 2025’s LLM Revolution: From GPT-2 to Kimi 2 Architectures Explained
2 months ago 高效码农From GPT-2 to Kimi 2: A Visual Guide to 2025’s Leading Large Language Model Architectures If you already use large language models but still get lost in technical jargon, this post is for you. In one long read you’ll learn: Why DeepSeek-V3’s 671 B parameters run cheaper than Llama 3’s 405 B How sliding-window attention lets a 27 B model run on a Mac Mini Which open-weight model to download for your next side project Table of Contents Seven Years of the Same Backbone—What Actually Changed? DeepSeek-V3 / R1: MLA + MoE, the Memory-Saving Duo OLMo 2: Moving RMSNorm One …
How Lightning Attention Slashes AI Inference Costs: The MiniMax-M1 Breakthrough Explained
3 months ago 高效码农MiniMax-M1: How Lightning Attention is Revolutionizing Large Model Inference Efficiency AI Chips and Light Trajectories Introduction: Breaking Through Traditional Transformer Efficiency Barriers In artificial intelligence, large model inference efficiency has become a critical bottleneck limiting technological advancement. The traditional Transformer architecture faces inherent limitations in long-sequence processing due to the quadratic computational complexity of its softmax attention mechanism. MiniMax’s newly released MiniMax-M1 model achieves unprecedented efficiency breakthroughs through innovative hybrid architecture while maintaining cutting-edge reasoning capabilities. The core of this technological breakthrough lies in lightning attention mechanism, combined with a Mixture-of-Experts (MoE) system, enabling the model to process million-token contexts …