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.