TRANSFORMERS & LLMs • 48 / 397
Follow text from characters to tokens, attention, transformers and generation.
Multi-Head Attention
Multi-head attention runs several attention heads in parallel so the layer can learn different relationships at once.
Think of it like
Think of Multi-Head Attention as part of a very fast reader that repeatedly decides what information matters and what should come next.
Real life
Autocomplete, translation and chat assistants depend on concepts such as Multi-Head Attention.
SRE lens
Multiple learned views help the model connect syntax, references and technical relationships.
Remember thisMulti-head attention runs several attention heads in parallel so the layer can learn different relationships at once.