Skip to content
ModelListedExternal
Download

Swiss German Whisper Ggml

Ready-to-use whisper.cpp / GGML build of a Swiss German speech-to-text model. Transcribe Swiss German audio into written Standard German locally on a Mac — no cloud, no API key.

KindOtherBase modelFlurin17/whisper-large-v3-turbo-swiss-germanVersionRevision b2fd4f5

Model source

Kind
Other
File size
547 MB–1.51 GB
Base model
Flurin17/whisper-large-v3-turbo-swiss-german
Version
vRevision b2fd4f5
Updated
Sep 22, 2026
Downloads
0
Source
Hugging Face

Source description

Swiss German Whisper — GGML build (unofficial)

Ready-to-use whisper.cpp / GGML build of a Swiss German speech-to-text model. Transcribe Swiss German audio into written Standard German locally on a Mac — no cloud, no API key.

This is a format conversion, not a new model. I did not train it. The weights are Flurin17's fine-tune of OpenAI Whisper large-v3-turbo; this repo only converts them to the GGML format that Mac apps like MacWhisper can load. Full credit below.

⚠️ License: non-commercial (CC-BY-NC-4.0)

Inherited from the source model. Free for personal / non-commercial use with attribution. No commercial use. Commercial use requires separate permission from the original author (Flurin17).

Files

FileSizeUse it if...sha256
ggml-model.bin1.5 GBbest quality (fp16)e147fd5c5979a260b5ce3e0bff493918b14af58101f12cee9620f7f067e347c4
ggml-model-q5_0.bin547 MBolder Mac / less RAM (quantized)2d56e773724a247360067b527417842b81d25ff891fed014341a6844f15ea612

Verify after download:

shasum -a 256 ggml-model.bin

Use it — no terminal needed (MacWhisper)

  1. Download one of the .bin files.
  2. MacWhisper → Settings → Models → Add custom model → pick the file.
  3. Set the language to German and transcribe.

Outputs written Standard German (Hochdeutsch), not dialect spelling. superwhisper and Whisper Notes load custom GGML models the same way.

Use it from the command line (whisper.cpp)

./build/bin/whisper-cli -m ggml-model.bin -f your-audio.wav -l de

Audio must be 16 kHz mono WAV:

ffmpeg -i input.m4a -ar 16000 -ac 1 -c:a pcm_s16le your-audio.wav

Limitations

  • Trained mainly on parliamentary / read speech — spontaneous everyday dialect and heavy accents are harder.
  • Outputs Standard German, not Swiss German spelling; use -l de, not --translate.
  • Like all Whisper models it can hallucinate on silence or noise.
  • Accuracy varies by dialect. Measure it on your own audio.

Model details

  • Base: OpenAI Whisper large-v3-turbo (n_mels 128, 32 audio / 4 text layers, vocab 51866).
  • Converted with whisper.cpp v1.9.1-75-g0ae02cdb via convert-h5-to-ggml.py.
  • Integrity verified: model loads and reports the expected turbo dimensions.

Credits

  • Fine-tuned model: Flurin17/whisper-large-v3-turbo-swiss-german — CC-BY-NC-4.0
  • Base model: OpenAI Whisper large-v3-turbo — MIT
  • Inference & GGML format: whisper.cpp by Georgi Gerganov & contributors — MIT
  • Datasets referenced by the source model: SwissDial (ETH Zürich), Swiss Parliaments Corpus V2 (FHNW), All Swiss German Dialects Test Set (FHNW), ArchiMob (University of Zürich)

If you are one of the authors above and want a change to how this is credited or distributed, please open a discussion — happy to adjust.

License

Distributed under CC-BY-NC-4.0, inherited from the source model.

Sources

1 source
Hugging FacePrimaryVersion b2fd4f5cc842dca6ed983825f0aea9cb13c72b7b
huggingface.co/gariwat/swiss-german-whisper-ggml/tree/b2fd4f5cc842dca6ed983825f0aea9cb13c72b7b

Verified Sep 22

Model artifacts

2 artifacts

ggml-model-q5_0.bin

bin · 547 MB · SHA-256 2d56e773724a…a612 · Hugging Face

Download

ggml-model.bin

bin · 1.51 GB · SHA-256 e147fd5c5979…47c4 · Hugging Face

Download

Source excerpts

2 excerpts

--- license: cc-by-nc-4.0 base_model: Flurin17/whisper-large-v3-turbo-swiss-german language: - gsw - de library_name: whisper.cpp pipeline_tag: automatic-speech-recognition tags: - whisper.cpp - ggml - swiss-german - schweizerdeutsch - speech-to-text - asr --- # Swiss German Whisper — GGML build (unofficial) Ready-to-use [whisper.cpp](https://github.com/ggml-org/whisper.cpp) / **GGML** build of a Swiss German speech-to-text model. Transcribe Swiss German audio into written Standard German **locally on a Mac** — no cloud, no API key. > **This is a format conversion, not a new model.** I did not train it. The weights are > Flurin17's fine-tune of OpenAI Whisper `large-v3-turbo`; this repo only converts them to > the GGML format that Mac apps like MacWhisper can load. Full credit below. ## ⚠️ License: non-commercial (CC-BY-NC-4.0) Inherited from the source model. Free for **personal / non-commercial** use with attribution. **No commercial use.** Commercial use requires separate permission from the original author (Flurin17). ## Files | File | Size | Use it if… | sha256 | |---|---|---|---| | `ggml-model.bin` | 1.5 GB | best quality (fp16) | `e147fd5c5979a260b5ce3e0bff493918b14af58101f12cee9620f7f067e347c4` | | `ggml-model-q5_0.bin` | 547 MB | older Mac / less RAM (quantized) | `2d56e773724a247360067b527417842b81d25ff891fed014341a6844f15ea612` | Verify after download: ```bash shasum -a 256 ggml-model.bin ``` ## Use it — no terminal needed (MacWhisper) 1. Download one of the `.bin` files. 2. MacWhisper → Settings → Models → **Add custom model** → pick the file. 3. Set the language to **German** and transcribe. Outputs **written Standard German** (Hochdeutsch), not dialect spelling. superwhisper and Whisper Notes load custom GGML models the same way. ## Use it from the command line (whisper.cpp) ```bash ./build/bin/whisper-cli -m ggml-model.bin -f your-audio.wav -l de ``` Audio must be 16 kHz mono WAV: ```bash ffmpeg -i input.m4a -ar 16000 -ac 1 -c:a pcm_s16le your-audio.wav ``` ## Limitations - Trained mainly on **parliamentary / read speech** — spontaneous everyday dialect and heavy accents are harder. - Outputs **Standard German**, not Swiss German spelling; use `-l de`, not `--translate`. - Like all Whisper models it can **hallucinate on silence or noise**. - Accuracy varies by dialect. Measure it on your own audio. ## Model details - Ba...

Source context: 0 downloads · 1 likes · Pipeline automatic-speech-recognition · Library whisper.cpp · Repo gariwat/swiss-german-whisper-ggml