---

library_name: transcribe.cpp

pipeline_tag: automatic-speech-recognition

license: other

license_name: swissdial-cc-by-nc-4.0-no-reidentification

license_link: https://form.jotform.com/223344961502048

language:

- gsw

- de

tags:

- gguf

- transcribe.cpp

- whisper

- q8_0

- swiss-german

- automatic-speech-recognition

base_model:

- openai/whisper-large-v3

- Flurin17/whisper-large-v3-peft-swiss-german

---

Whisper Large-v3 Swiss German – GGUF Q8_0

Q8_0-quantized GGUF conversion of openai/whisper-large-v3 with the LoRA

adapter Flurin17/whisper-large-v3-peft-swiss-german merged into the weights.

This is a standalone checkpoint for

handy-computer/transcribe.cpp.

Usage

ffmpeg -i input.m4a -ar 16000 -ac 1 input.wav

build/bin/transcribe-cli \
  -m whisper-large-v3-swiss-german-Q8_0.gguf \
  --language de \
  input.wav

For Swiss German transcription, de is the recommended Whisper language token

and transcribe is the intended task.

Format and compatibility

• Format: GGUF Q8_0
• Runtime: handy-computer/transcribe.cpp
• Source quantization: the validated F16 GGUF variant
• Not compatible with oMLX, which expects MLX Safetensors

Use

gcoli/whisper-large-v3-swiss-german-mlx-fp16

for oMLX.

Provenance

• Base revision: 1ecca609f9a5ae2cd97a576a9725bc714c022a93
• Adapter revision: 2ae117cf342bc57d6068066181a9d359e98a2961
• transcribe.cpp converter and quantizer revision:

856d7c10a1a864b900e066b7c9801edf373f5148

• Quantization preset: Q8_0

The adapter was merged into the base model in FP16. The resulting F16 GGUF was

then quantized using transcribe-quantize. Tokenizer, frontend and model

metadata remain embedded in the GGUF. quantization_provenance.json records

the exact F16 source checksum.

Evaluation and limitations

The build performs checksum validation and a real runtime transcription test.

Independent Swiss German WER and controlled performance comparisons between

F16 and Q8_0 have not yet been published. Quantization can introduce small

accuracy differences.

Whisper can hallucinate or omit text, particularly with noise, silence,

overlapping speakers, uncommon dialects, or specialized vocabulary. Do not use

its output as the sole basis for high-impact decisions.

License and usage conditions

SwissDial CC BY-NC 4.0 with no-reidentification condition

The Swiss German adaptation was trained on the

SwissDial dataset.

Use is limited to non-commercial purposes under CC BY-NC 4.0, attempts to

re-identify SwissDial speakers are prohibited, and SwissDial must be attributed

and cited in research use.

The Whisper base model remains subject to Apache-2.0. This repository grants no

additional rights to upstream models, training data, or software.