ThakiCloud/eg2-text-q4

Feature Extraction • 0.1B • Updated 2 days ago • 45

Note 4-bit text tower, 152,669,232 B of weights. Keeps 0.936 of the BF16 top-10 neighborhood (BF16 = 1.000); margin 0.1712 vs BF16 0.1817. Internally measured on a private frozen set; serving not validated.

ThakiCloud/eg2-text-hybrid-129m

Feature Extraction • 0.1B • Updated 2 days ago • 28

Note Mixed-precision text tower (GPTQ 4-bit transformer, 2-bit vocabulary with 30% of rows at 4-bit), 129,532,796 B — 85% of eg2-text-q4. Beats uniform 3-bit on every held-out slice; within 25% of the 3→4-bit gap of the Q4 recipe. Internally measured; serving not validated.

ThakiCloud/eg2-text-hybrid-119m

Feature Extraction • 0.1B • Updated 2 days ago • 15

Note Size-oriented mixed-precision text tower (GPTQ 4-bit transformer, 2-bit vocabulary, no row rescue), 119,152,312 B. At the uniform-3-bit byte budget it wins all 8 held-out cells over uniform 3-bit, and it gives up most of the 4-bit advantage on multilingual and rare-identifier retrieval. Internally measured; serving not validated.

Note Why this line allocates bits the way it does. The embedding table never emerges as the dominant isolated protection priority in any of the four families measured, and at INT4/g16 the spread between modules is too small to allocate against. Measures EmbeddingGemma-300M, not EmbeddingGemma 2.

Note The label-free drift signal this line's mixed-precision allocation descends from, measured on five development embedders including EmbeddingGemma-300M. EmbeddingGemma 2 itself is not in that paper's grid.