How to Build a Large Language Model
Step-by-Step Guide to Creating Your Own AI Model Using Transformers, Datasets, and PythonBy Rachel Bennett
Length2h 43m
About this audiobook
Step into the world of modern AI and discover how powerful language models are created. How to Build a Large Language Model offers a clear roadmap for designing, training, and deploying advanced systems based on Large Language Model technology.
Whether you're a developer, researcher, or AI enthusiast, this guide explains how modern Artificial Intelligence systems evolve from simple rule-based programs to the transformer architecture that powers today’s most advanced models. You’ll learn how to prepare data, train models efficiently, evaluate performance, and deploy scalable AI systems for real-world use.
Here's a Preview of What You'll Learn...
Understanding transformer architecture behind modern LLMs
Addressing bias, fairness, and ethical considerations
Deploying language models at scale
Future trends shaping the next generation of AI
Gain the knowledge to move from understanding AI models to building your own.
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Audiobook details
GenreTechnology, Self-Help
Length2 hrs 43 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateMar 8, 2026
LanguageEnglish
Table of contents
1Introduction
10Optimization Techniques and Loss Functions
2Introduction to Language Models and Their Impact
11Evaluation Metrics and Benchmarking Performance
3From Rule-Based to Neural Nets: A Brief History
12Addressing Bias, Fairness, and Ethical Concerns
4Understanding Transformers: The Architecture Behind LLMs
13Deployment: Serving LLMs at Scale
5Data Collection: Building the Right Dataset
14Cost and Resource Management in LLM Development
Show all chaptersShow less
6Data Preprocessing and Tokenization
15Building for Specific Tasks: Chatbots, Summarizers, and More
7Choosing Model Size and Architecture
16The Future of Large Language Models
8Training Infrastructure: Hardware and Frameworks
17Conclusion
9Fine-Tuning vs. Training from Scratch
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