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Non-Uniform Period Scaling in RoPE Base Scaling
When the base in Rotary Positional Embeddings (RoPE) is scaled, it results in a non-uniform adjustment of the periods across the different dimensions of the frequency parameter vector . This means that each dimension's period is scaled by a different amount.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Ch.2 Generative Models - Foundations of Large Language Models
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Period Matching Constraint for RoPE Base Scaling
Non-Uniform Period Scaling in RoPE Base Scaling
A language model, pre-trained on a maximum sequence length of
L, uses rotary position encodings where the frequencies are derived from a shared base parameter,b. To adapt this model to handle a new, longer maximum sequence length of4Lwhile preserving its relative positional understanding, an engineer decides to modify only the base parameter. How should the new base,b', relate to the original base,b?When a language model's context length is extended by scaling the base parameter of its rotary position embeddings, the rotational period for every dimension of the embedding is increased by the exact same factor.
Mechanism of RoPE Base Scaling
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A developer is adapting a pre-trained language model that uses rotational position embeddings to handle much longer input sequences. They achieve this by applying a scaling factor to the base
bused in the frequency calculations for the embeddings. Which statement best analyzes the impact of this change on the periods of the rotational frequencies across the different embedding dimensions?When the base
bused to calculate frequency parameters in Rotary Positional Embeddings is multiplied by a scaling factor, the periods associated with all dimensions of the embedding are scaled by an identical, uniform amount.Analysis of Period Scaling in Positional Embeddings