Getting Started with Local LLMs
Chapter 1: Introduction to Large Language Models
What Is a Large Language Model (LLM)?
A Simple View of How LLMs Work
Understanding Tokens and Text Generation
Why Run LLMs Locally?
Local vs. Cloud-Based LLMs
Chapter 2: Preparing Your Local Environment
Hardware Considerations: CPU
Hardware Considerations: RAM
Hardware Considerations: GPU and VRAM
Checking Your System Specifications
Operating System Compatibility
Installing Python (Optional but Recommended)
Introduction to the Command Line / Terminal
Chapter 3: Finding and Selecting Local LLMs
Where to Find LLM Models: Hugging Face Hub
Understanding Model Sizes and Parameters
Model Formats: GGUF and Others
Quantization: Making Models Smaller
Reading Model Cards for Information
Model Licenses and Usage Restrictions
Choosing Your First Model
Chapter 4: Running Your First Local LLM
Introduction to Local LLM Runners
Setting up Ollama
Downloading a Model with Ollama
Running a Model with Ollama (Command Line)
Setting up LM Studio
Finding and Downloading Models in LM Studio
Loading and Chatting with a Model in LM Studio
Introduction to llama.cpp (Concept)
Hands-on Practical: Running a Model
Chapter 5: Basic Interaction and Prompting
What is a Prompt?
Your First Prompt: Simple Questions
Giving Instructions
Understanding Context Window
Basic Prompt Formatting Tips
Temperature and Creativity
Common Interaction Patterns
Practice: Simple Prompting Techniques
Introduction to Large Language Models
This chapter focuses on the fundamentals of Large Language Models (LLMs). We start by defining what an LLM is and offer a simplified explanation of its text generation process. You will learn about tokens, the building blocks of text for these models. The chapter concludes by discussing the advantages of running LLMs locally and comparing local operation with cloud-based alternatives. By the end of this chapter, you will have a clear understanding of the core concepts needed before setting up your own local environment.
Sections
1.1 What Is a Large Language Model (LLM)?
1.2 A Simple View of How LLMs Work
1.3 Understanding Tokens and Text Generation
1.4 Why Run LLMs Locally?
1.5 Local vs. Cloud-Based LLMs
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