ZIPA Large CR-CTC NS No-Diacritics 780k — TurboQuant TQ4 (native Metal)

What this is

• Base model: anyspeech/zipa-large-crctc-ns-no-diacritics-780k (300M params, Zipformer CR-CTC non-streaming, no diacritics).
• Quantization: TurboQuant TQ4_1S — 4-bit, 32-value blocks with a Randomized Hadamard Transform front-end, dual half-block fp16 scales, and Lloyd-Max-optimal Gaussian centroids. The 410 Linear weights are quantized; convs / norms / biases / bypass scales / linear_pos stay f32.
• Runtime: consumed by helix-metal's zipa_metal::ZipaModel — the quantized weights stay TQ4-resident in Metal (no dequant), and the split <name>.scales / <name>.qs tensors are 16 KiB page-aligned so they're aliased zero-copy from the mmap via newBufferWithBytesNoCopy.
• Size: ~204 MB (≈180 MB data + page-alignment padding). On-disk == resident.

Layout

model.safetensors   bundle tensors + embedded `turboquant.index` (header metadata):
                      <name>.scales / <name>.qs   (u8, split TQ4 blocks) per Linear
                      conv2d (OHWI) / norms / biases / bypass / downsample (f32)
tokens.txt          CTC phone vocabulary (id → IPA unit)
config.json         architecture + quantization metadata

Quality

Provenance