Same weights as
prashanthsura/gemma-2-2b-legal-financial-sft except the tied
token-embedding matrix (256000 x 2304, ~590M params, ~22.6% of the model) has
been replaced by its 2-stage Residual Product Quantization reconstruction
(M=384 subspaces, K=1024 codewords per stage, L=2 stages ->
3.59 bits/param for that matrix vs 16 in bf16). Because Gemma ties
its output head to the embedding, one codebook covers both roles ("unified
codebook").
