windy-core-ggml / README.md
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correct licence to apache-2.0 (matches upstream base)
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---
license: apache-2.0
base_model: openai/whisper-small
tags: [whisper, whisper.cpp, ggml, automatic-speech-recognition, windyword, mobile, quantized]
library_name: whisper.cpp
---
# Windy Core — ggml q5_1 (mobile build)
**Windstorm Labs is the origin of record for this artifact.** It is created
here and promoted downstream; it is never edited anywhere else.
`whisper.cpp` / `whisper.rn` build of Windy Core, quantized to **q5_1** so it runs
on phones and tablets.
| | |
|---|---|
| File | `ggml-windy-core-q5_1.bin` |
| Size | **190.1 MB** |
| SHA-256 | `924cf246d2a9773554f1546dbdc7bb272de6ec8fe6dca9a774ae60047b24ca7c` |
| Quantization | q5_1 |
| Languages | **multilingual** |
| Certified WER | 5.85% (grade A) |
## Lineage
| Stage | Value |
|---|---|
| Upstream base | [`openai/whisper-small`](https://huggingface.co/openai/whisper-small) (244M params, MIT) |
| Windy fine-tune | LoRA, merged — Clinic patient `windy-core` |
| Converted from | [`WindyWord/listen-windy-core`](https://huggingface.co/WindyWord/listen-windy-core) @ `0781aae8f000814b6571a4c227fad6685b04de64` |
| Converter | `whisper.cpp` @ `2ca53bb45e38`, `models/convert-h5-to-ggml.py` -> `whisper-quantize q5_1` |
| Built on | Veron-1-5090, 2026-08-01 |
## Promotion path
`WindstormLabs` (here, origin) -> `WindyWord` (product) -> `WindyWordMobileApp` (mobile).
Downstream copies are **push-only**. Fix weights here, never downstream.
## Honesty note
Distinct weights from upstream (different SHA-256). On short clean English
clips the smaller models can be indistinguishable from stock Whisper — a
formal bake-off has **not** been run. Do not claim quality gains without one.
Clinic patient file: `sneakyfree/Windy-Clinic` -> `stt-models/windy-core.json`
## Licence
Upstream base is **apache-2.0** on Hugging Face, verified against the source repo we converted from. Note OpenAI's Whisper *GitHub* repo states MIT while its HF model cards state Apache-2.0; we follow the HF distribution point, since that is what we actually pulled. Windy weights are a derivative and are distributed under the same terms, with attribution upstream.