In-depth explanation of the new Byte Latent Transformer architecture, for token-free transformers. Without a tokenizer new methods at the local attention level have to define the byte patching functions via an entropy based prediction for next byte. Explanation of the inner workings of the local Encoder, including its causal local attentions and the cross-attention mechanisms for byte pooling for latent patches.
All rights w/ authors:
"Byte Latent Transformer: Patches Scale Better Than Tokens"
Artidoro Pagnoni, Ram Pasunuru, Pedro Rodriguez, John Nguyen, Benjamin Muller, Margaret Li, Chunting Zhou, Lili Yu, Jason Weston, Luke Zettlemoyer, Gargi Ghosh, Mike Lewis, Ari Holtzman, Srinivasan Iyer
FAIR at Meta, Paul G. Allen School of Computer Science & Engineering, University of Washington, University of Chicago
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