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LLMs Explained
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0. Start Here
What Is an LLM?
The Life Cycle at a Glance
1. Data
Where the Data Comes From
Filtering & Cleaning
2. Tokenization
What Are Tokens?
Tokenizer Playground
3. Training
Chunking & Packing
Next-Token Prediction
From Autocomplete to Assistant
4. Inference and the API
Anatomy of an API Call
Conversations Are Stateless
Sampling & the Context Window
5. Tools and Harnesses
Tool Use
The Harness Loop
6. Agents
What Is an Agent?
Coding Agents
Agent Security
Appendix
Glossary
Further Reading
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Glossary
What this page will cover
Section titled “What this page will cover”
Token, context window, parameter/weight, pretraining, fine-tuning, RLHF
Inference, temperature, system prompt, tool use, harness, agent, RAG, prompt injection