What Are Large Language Models (LLMs)?

📰 Medium · LLM

Learn the basics of Large Language Models (LLMs) and how they work, including tokenization, embeddings, and fine-tuning, to understand their potential and limitations.

beginner Published 4 Jul 2026

Action Steps

Read about the basics of LLMs and their applications
Understand the role of transformers in LLMs and how they enable self-attention
Apply tokenization and embeddings to text data using popular libraries like NLTK or spaCy
Experiment with fine-tuning pre-trained LLMs for specific tasks using frameworks like TensorFlow or PyTorch
Evaluate the performance of LLMs on various tasks and datasets to identify their strengths and weaknesses

Who Needs to Know This

Data scientists, software engineers, and product managers can benefit from understanding LLMs to develop and implement AI-powered solutions, and to make informed decisions about their use cases.

Key Insight

💡 LLMs are powerful AI models that can generate human-like text, but they require careful training, fine-tuning, and evaluation to achieve optimal results.

Key Takeaways

Learn the basics of Large Language Models (LLMs) and how they work, including tokenization, embeddings, and fine-tuning, to understand their potential and limitations.

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Title: What Are Large Language Models (LLMs)?

URL Source: https://dondew.medium.com/what-are-large-language-models-llms-096974427f6d?source=rss------llm-5

Published Time: 2026-07-04T17:10:11Z

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1. [1. So, What Exactly Is an LLM?](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#6b56 "1. So, What Exactly Is an LLM?")
2. [2. The Engine Behind LLMs: Transformers](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#6f65 "2. The Engine Behind LLMs: Transformers")
3. [What is self-attention?](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#2a07 "What is self-attention?")
4. [3. How LLMs Actually Read Text: Tokens and Embeddings](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#4678 "3. How LLMs Actually Read Text: Tokens and Embeddings")
5. [Step 1: Tokenization](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#6957 "Step 1: Tokenization")
6. [Step 2: Embeddings](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#a359 "Step 2: Embeddings")
7. [4. How Does an LLM Learn All This?](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#c470 "4. How Does an LLM Learn All This?")
8. [Phase 1: Pretraining](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#beb9 "Phase 1: Pretraining")
9. [Phase 2: Fine-Tuning](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#5f64 "Phase 2: Fine-Tuning")
10. [5. How Does an LLM Generate a Response?](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#dcc7 "5. How Does an LLM Generate a Response?")
11. [6. Why Are LLMs Such a Big Deal?](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#0976 "6. Why Are LLMs Such a Big Deal?")
12. [7. But LLMs Aren’t Perfect](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#0604 "7. But LLMs Aren’t Perfect")
13. [Wrapping Up](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#5276 "Wrapping Up")
14. [References](https://dondew.medium.com/?source=post_page-----096974427f6d---------------------------------------#a7d4 "References")

LLM

Fine Tuning

Transformers

Tokenization

Pre Training

# **What Are Large Language Models (LLMs)?**

[![Image 2: Don Dew](http

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What Are Large Language Models (LLMs)?

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