Meta and Stanford Researchers Propose Fast Byte Latent Transformer That Reduces Inference Memory Bandwidth by Over 50% Without Tokenization
A workforce of researchers from Meta, Stanford University, and the University of Washington have launched three new strategies that considerably speed up era within the Byte Latent Transformer (BLT) — a language mannequin structure that operates straight on uncooked bytes as an alternative of tokens. Byte-Level Models Are Slow at Inference To perceive what this…
