A transformer model's architecture specifies that its token embeddings have a dimensionality of 768. This model uses a rotational method to encode positional information, where the transformations are governed by a specific parameter vector. Based on this information, how many components does this parameter vector contain?

Consequences of Modifying RoPE Parameters

In a model that uses rotational transformations to encode positional information, if the token embeddings have a dimensionality of d, the parameter vector θ that governs these transformations will also have d components.