Perceiver ✦

The Perceiver treats text as a sequence of raw bytes rather than traditional word-level tokens, allowing it to understand the meaning of text directly from its individual characters.

: It makes no prior assumptions about the structure of text, applying the same attention mechanisms it would use for an image or audio file. perceiver

: The model uses a small set of "latent" variables to attend to the much larger input text. This "cross-attention" step decouples the depth of the network from the size of the input, making it much faster for long documents. The Perceiver treats text as a sequence of

Unlike standard Transformers, which face high computational costs as input size increases, the Perceiver uses a to efficiently handle large amounts of data. How the Perceiver Works with Text This "cross-attention" step decouples the depth of the