What is Learned Position Embeddings? Why does it exist? Where does it appear in Positional Information?
Draw or describe a visual model of Learned Position Embeddings. What does it look like conceptually?
Work through a concrete manual example of Learned Position Embeddings with real numbers or pseudocode.
How is Learned Position Embeddings different from related concepts in Positional Information? What are the trade-offs?
Explain Learned Position Embeddings in plain language using an analogy. Could a non-expert follow it?
tiny_llm/transformer.py
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