Transformers & LLMs
Attention mechanisms, large language models, and multimodal architectures: the building blocks of modern AI.
- LLM
- 28 concepts
Attention basics
Start with tokens, follow an attention calculation, then decide where queries can read.
Starting knowledge: Vectors, matrix multiplication and probability distributions
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Previewing Tokenization.
Turn text into model inputs
Explore how text becomes token IDs before following the computations over their embeddings.
Turn text into model inputs
Tokenization
Trace BPE merges and compare tokenization methods, normalization and the token budget.
Read conceptUsed in: connections 1 to 2 of 2.
Compute attention and control visibility
Build the scaled dot-product calculation, run it across heads, then block future keys for causal prediction.
Read from another source
Use the same attention calculation with queries from one sequence and keys and values from another.
Lines show suggested reading within a branch. Connections offer optional ways to explore; they are not a checklist of prerequisites.
