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
1ffmpeg -i input.m4a -ar 16000 -ac 1 input.wav
2
3build/bin/transcribe-cli \
4 -m whisper-large-v3-swiss-german-Q8_0.gguf \
5 --language de \
6 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
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.
