Inside the Transformer

Mastering Large Language Models through Neural Exploration.

latent_space_navigator
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Processing Tensors...

Layer:LLMs don't read words like humans. They see 'Tokens'. Each word or sub-word is converted into a number (Vector).

LLM Architecture

Unlock the layers of large-scale language modeling.

Base Models

A base model is trained on a massive chunk of the internet to predict the next token. It knows facts, but doesn't know how to follow directions yet. If you ask it 'What is the capital of France?', it might reply with 'And what is the capital of Germany?' because it thinks it's looking at a list of questions.

Inference Logic Check

What is the primary objective of a 'Base' model during pre-training?


AI Concept Glossary

Tokens
The smallest units of text processed by an LLM. Common tokens include 'the', 'ing', or punctuation marks.
Context Window
The maximum amount of tokens a model can 'remember' at one time during a conversation.
Self-Attention
The mechanism that allows a Transformer to relate different words in a sentence regardless of their distance from each other.
Parameters
The internal variables (weights) learned during training that determine how the model processes input.