Beginner-Friendly Explanation of Large Language Models
Published:Jan 2, 2026 13:09
•1 min read
•r/OpenAI
Analysis
The article announces the publication of a blog post explaining the inner workings of Large Language Models (LLMs) in a beginner-friendly manner. It highlights the key components of the generation loop: tokenization, embeddings, attention, probabilities, and sampling. The author seeks feedback, particularly from those working with or learning about LLMs.
Key Takeaways
- •The article provides a link to a blog post explaining LLMs.
- •The explanation is designed to be beginner-friendly.
- •The blog post covers tokenization, embeddings, attention, probabilities, and sampling.
- •The author welcomes feedback.
Reference
“The author aims to build a clear mental model of the full generation loop, focusing on how the pieces fit together rather than implementation details.”