juniorLLMs

What is a token embedding?

Updated May 16, 2026

Short answer

Token embeddings are dense vector representations of tokens in a continuous space.

Deep explanation

Embeddings convert discrete tokens into continuous vectors that capture semantic meaning. Similar words have similar embeddings. These vectors are learned during training and are essential for downstream transformer computations.

Real-world example

Words like 'king' and 'queen' have similar embedding structures.

Common mistakes

Assuming embeddings are static or predefined.

Follow-up questions

What is cosine similarity?
Why embeddings are important?

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