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---
license: apache-2.0
language:
- de
library_name: mlx
pipeline_tag: automatic-speech-recognition
model-index:
- name: mlx version of whisper-large-v3-turbo-german by Florian Zimmermeister @primeLine
results:
- task:
type: automatic-speech-recognition
name: Speech Recognition
dataset:
name: German ASR Data-Mix
type: flozi00/asr-german-mixed
metrics:
- type: wer
value: 2.628 %
name: Test WER
datasets:
- flozi00/asr-german-mixed
- flozi00/asr-german-mixed-evals
base_model:
- primeline/whisper-large-v3-german
---
# whisper-large-v3-turbo-german-f16
This model was converted to MLX format from primeline/whisper-large-v3-turbo-german
made with a [custom script for converting safetensor whisper models](https://github.com/CrispStrobe/mlx-examples/blob/main/whisper/convert_safetensors.py).
it is in float16, works well. quantized version: [4bit, float16](https://huggingface.co/mlx-community/whisper-large-v3-turbo-german-f16-q4)
## Use with MLX
```bash
git clone https://github.com/ml-explore/mlx-examples.git
cd mlx-examples/whisper/
pip install -r requirements.txt
```
```python
import mlx_whisper
result = mlx_whisper.transcribe("test.mp3", path_or_hf_repo="mlx-community/whisper-large-v3-turbo-german-f16")
print(result)
``` |