initial release

quantize.sh

@@ -0,0 +1,37 @@
+#!/bin/bash
+# Derive lighter GGUFs from the F32 source-of-truth produced by convert.py.
+#   omnivoice-base-F32.gguf       -> BF16, Q8_0, Q4_K_M
+#   omnivoice-tokenizer-F32.gguf  -> BF16, Q8_0, Q4_K_M
+#
+# Three variants cover the useful precision range : BF16 for max precision
+# on CUDA, Q8_0 as the balanced default, Q4_K_M as the smallest variant
+# that still sounds correct. Q5_K_M / Q6_K were tested and dropped : their
+# size sits between Q4_K_M and Q8_0 with negligible perceptual gain.
+#
+# Quantization policy is centralized in tools/quantize.cpp should_quantize :
+# RVQ codebooks (quantizer.quantizers.*) and the fc / fc2 linear projections
+# wrapping them stay at F32 in every variant. Nearest-neighbor lookup is
+# sensitive to per-row quantization noise ; even BF16 mantissa truncation
+# drifts codes enough to break voice cloning. Conv weights stay at source
+# dtype and are cast to F16 at load time by gf_load_conv_f16 (ARM im2col
+# strict). Same policy as acestep.cpp keeping VAE-critical paths intact.
+
+set -eu
+
+Q="./build/quantize"
+
+quantize() {
+    local src="$1" type="$2"
+    local out="${src/-F32.gguf/-${type}.gguf}"
+    if [ -f "$out" ]; then
+        echo "[Skip] $out"
+    else
+        $Q "$src" "$out" "$type"
+    fi
+}
+
+for src in models/omnivoice-base-F32.gguf models/omnivoice-tokenizer-F32.gguf; do
+    quantize "$src" BF16
+    quantize "$src" Q8_0
+    quantize "$src" Q4_K_M
+done