Fixed 16-bit binary token codes can replace trainable input embeddings in 32-layer decoder-only models while maintaining comparable held-out perplexity on 17B tokens.
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Language Models Without a Trainable Input Embedding Table: Learning from Fixed Minimal Binary Token Codes
Fixed 16-bit binary token codes can replace trainable input embeddings in 32-layer decoder-only models while maintaining comparable held-out perplexity on 17B tokens.