2025 Open-Weight LLM Guide: Architecture Innovations and Practical Deployment
1 days ago 高效码农The 2025 Landscape of Open-Weight Large Language Models: A Plain-English Tour from DeepSeek-V3 to Kimi 2 “Seven years after the first GPT paper, are we still stacking the same Lego blocks?” “Which model can I actually run on a single RTX 4090?” “What do MoE, MLA, NoPE, and QK-Norm mean for my weekend side-project?” This article answers those questions in plain language. Every fact, number, and code snippet comes from the official papers or repositories of the eight model families discussed—no outside sources, no hype. Table of Contents Why Architecture Still Matters in 2025 One Map, Eight Models Model-by-Model Walk-Through …
LLM vs LCM: How to Choose the Right AI Model for Maximum Project Impact
2 months ago 高效码农LLM vs LCM: How to Choose the Optimal AI Model for Your Project AI Models Table of Contents Technical Principles Application Scenarios Implementation Guide References Technical Principles Large Language Models (LLMs) Large Language Models (LLMs) are neural networks trained on massive text datasets. Prominent examples include GPT-4, PaLM, and LLaMA. Core characteristics include: Parameter Scale: Billions to trillions of parameters (10^9–10^12) Architecture: Deep bidirectional attention mechanisms based on Transformer Mathematical Foundation: Sequence generation via probability distribution $P(w_t|w_{1:t-1})$ Technical Advantages Multitask Generalization: Single models handle tasks like text generation, code writing, and logical reasoning Context Understanding: Support context windows up to …