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    Home»Machine Learning»The Byte Latent Transformer: A New Paradigm in Language Modeling? | by Manuele Caddeo | Dec, 2024
    Machine Learning

    The Byte Latent Transformer: A New Paradigm in Language Modeling? | by Manuele Caddeo | Dec, 2024

    Team_AIBS NewsBy Team_AIBS NewsDecember 15, 2024No Comments1 Min Read
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    Latest developments in pure language processing have been largely pushed by transformer-based fashions that depend on tokenization — breaking textual content into predefined subword items. Nonetheless, a groundbreaking new strategy referred to as the Byte Latent Transformer (BLT) is difficult this conference, providing a extra versatile and environment friendly various.

    What’s BLT?

    The Byte Latent Transformer is a novel structure that processes uncooked byte knowledge instantly, eliminating the necessity for a hard and fast vocabulary or tokenization step. As a substitute, BLT dynamically teams bytes into “patches” based mostly on the complexity of the info

    Key options of BLT embody:

    • Dynamic patching: Bytes are grouped into patches of variable dimension based mostly on info density
    • Environment friendly compute allocation: Extra processing energy is utilized to complicated, high-entropy sections of textual content
    • Byte-level processing: Direct entry to character-level info, enhancing dealing with of uncommon phrases and multilingual textual content

    How Does It Work?

    BLT consists of three principal elements:

    1. Native Encoder: A light-weight transformer that converts enter bytes into patch representations
    2. International Latent Transformer: A big transformer that processes the patch representations
    3. Native Decoder: Converts patch representations again into…



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