Emulating ALiBi with Rope
LLMs usually use some sort of positional encoding for helping the model understand where different tokens — or more precisely, KV cache entries — are. Two of th...
Summary
Researchers discuss how to emulate ALiBi (Attention with Linear Biases) using Rope (Rotary Positional Embedding) in large language models. The paper details the mechanics of positional encoding and its impact on token processing.
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