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BuilderHelm/Kanso-Koi-0.8
Kanso-Koi-0.8 is a text generation model from BuilderHelm. Use it when you need the model to write or continue text. It is set up for mlx. The card lists the license as apache-2.0.
<div align="center" <img src="assets/kanso-koi.png" width="160" alt="Kanso Koi"/ </div
Downloads · 30 days
1K
94% of all-time downloads
All-time downloads
1.1K
Public
Parameters
1.7B
980 MB on disk
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.safetensors968 MB · 99%
How the weights are stored.
U321.7B · 100%
From the Hugging Face model README
Names. ZenVoice's formatting models are called Kanso since ZenVoice 1.3.1: Kanso Koi 1.0 was ZenPolish v2.2 Lite, Koi 0.9 was ZenPolish v2.2, Koi 0.8 was ZenPolish v2, Kanso Satori 1.0 was ZenPolish v3.2 4B and Satori 0.9 was ZenPolish v3 4B. The repositories were renamed from
zen-polish-…; old links and pinned revisions redirect here. Tables below use the development version numbers (v2, v2.1, v2.2, v3, v3.1, v3.2).
Retired. ZenVoice no longer offers this model; it stays here for earlier builds. Use Kanso-Koi-1.0 or Kanso-Satori-1.0.
ZenVoice's on-device dictation-enhancement model. Takes the raw, unpunctuated text produced by speech-to-text engines and restores everything dictation loses: punctuation, capitalization, filler removal, spoken numbers, dates, and times. Runs fully on-device on Apple Silicon via MLX — nothing leaves the Mac.
Base model: fine-tuned (LoRA) from Qwen3-1.7B, then merged and 4-bit quantized. Qwen3 is the starting point; the formatting behavior below is entirely the fine-tune.
ChatML prompt, thinking disabled:
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": "um yeah so we need to fix this bug by tuesday right check the pull request"},
]
# -> "Yeah, so we need to fix this bug by Tuesday, right? Check the pull request."
The exact system prompt is in the ZenVoice repository (training/common.py).
Measured on ZenVoice's frozen eval sets (training/evaluate.py with the
corrected word-only WER alignment and punctuation substitution accounting),
greedy decoding, vs. stock Qwen3-1.7B-Instruct under the same prompt.
300-row synthetic eval — Koi 0.8 vs stock base:
| Metric | Koi 0.8 | Stock base |
|---|---|---|
| WER | 5.0% | 10.1% |
| Exact match | 20.3% | 11.3% |
| Punctuation F1 | 0.391 | 0.143 |
| New-content (hallucination) rate | 3.1% | 4.3% |
| Capitalization accuracy | 94.2% | 89.9% |
Clean real-input bench (120 rows): Koi 0.8 7.6% WER vs stock 11.0%, exact match 7.5% vs 5.0% — v2 stays ahead of stock on clean input. Its WER is higher on clean input than on noisy ASR-style input (7.6% vs 5.0%); identity-mix training in v3 closes that gap.
Pipeline and recipe are in the ZenVoice repo under training/:
noisifier (spoken-form degradation of clean text), synthetic + real ASR
pair builders, frozen eval sets, mlx-lm LoRA training, and the gate
harness. Weights: 4-bit MLX safetensors, 934 MB.
Apache-2.0, inherited from the Qwen3-1.7B base.
Published under BuilderHelm AI. Previously imYChaudhary22/Kanso-Koi-0.8; existing repository links and pinned revisions redirect to this organization repository. Model filenames and weights are unchanged.