McBopomofoLM v3.1.2 models: decoder with next-token functions (n16-n96), dec_next_first.tsv

d8edfe6 verified 1 day ago

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license: apache-2.0
language:
  - zh
tags:
  - coreml
  - apple-neural-engine
  - input-method
  - zhuyin
  - bopomofo
base_model: Luigi/sloth-ime-models

McBopomofoLM models (Core ML, Apple Neural Engine)

Core ML conversions of the SlothE models used by McBopomofoLM (branch lm), a fork of McBopomofo that uses the models to improve candidate selection and to suggest corrections for mistyped syllables. Both models run on the Apple Neural Engine only (computeUnits = CPU_AND_NE).

Revisions: main and tag v3.1.2 match McBopomofoLM v3.1.x. Tag v2.1.1 is the runtime for McBopomofoLM v2.1.1, which has no next-token functions.

Path	What
`runtime/`	The exact runtime bundle shipped in McBopomofoLM v3.1.2 (`Contents/Resources/SlothE`): compiled `.mlmodelc`, embedding table, vocabularies, the next-token first-char table `dec_next_first.tsv`, and `runtime-manifest.txt`. The app checks the size and SHA-256 of each file against the manifest before it loads that file.
`mlpackage/enc25m_multi_pal2_emb.mlpackage`	SlothE-T 25M encoder, 2-bit palettized. The ternary weights make this lossless. Multifunction package with functions L8/L16/L32/L64/L256. The embedding lookup runs in the caller, from `runtime/enc25m_embed_f16.bin`.
`mlpackage/dec_mf_tn_fp16.mlpackage`	SlothE decoder `pred_q35_60m` (Qwen3.5 architecture), fp16, one weight file shared by two function families. t16/t32/t64/t96 (batch 3) return per-token log-probabilities of given texts; they are bit-identical to v2.1.1's decoder. n16/n32/n64/n96 (batch 1; input `ids` right-padded and `last` = index of the last real token) return the full next-token log-softmax over the 16k vocabulary. Gated DeltaNet runs in fixed 16-token chunks.
`scripts/`	Conversion and bundling scripts, research-grade. They import helpers from the author's research workspace, which is not included, so they document the conversion and do not run on their own. `MCBPMF_LM_WORK` sets the workspace root. `build_next.py` builds the n* functions; `build_dec_tn.py` merges them with the t* functions.

Measured on an M2 (ANE):

encoder: 100% of ops on the ANE, about 0.8 ms per call;
decoder t*: 86–95% on the ANE, 2.6–7.9 ms per call depending on length;
decoder n*: 83–94% on the ANE, 2.3–3.1 ms per call.

Against HF fp32 on CPU, the n* functions agree on the top-1 token for 95.5% of 288 prefixes; every mismatch is a near-tie. The largest log-prob difference over the top-50 tokens is 0.31 nats at the median and 0.73 at P95, from fp16 on the ANE. The first compile of all functions takes about 3 minutes.

Sources and licenses

Weights: Luigi/sloth-ime-models, Apache-2.0.
char2id.tsv: converted from enc/char2id.json in Luigi/slothing-web, Apache-2.0.
Variant classes: derived from OpenCC TWVariants.txt and HKVariants.txt, Apache-2.0.
Conversion: Apache-2.0 (LICENSE). See NOTICE.txt.

McBopomofoLM models (Core ML, Apple Neural Engine)

Contents

Sources and licenses