---
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-q4
This model was converted to MLX format from primeline/whisper-large-v3-turbo-german and is quantized to 4bit, float16.

made with a [custom script for converting safetensor whisper models](https://github.com/CrispStrobe/mlx-examples/blob/main/whisper/convert_safetensors.py). 

there is also an [unquantized float16](https://huggingface.co/mlx-community/whisper-large-v3-turbo-german-f16) version

## 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)
```

# whisper-large-v3-turbo-german-f16-q4
This model was converted to MLX format.

## Use with MLX

```bash
git clone https://github.com/ml-explore/mlx-examples.git
cd mlx-examples/whisper/
pip install -r requirements.txt

# Example usage
import mlx_whisper
result = mlx_whisper.transcribe("test.mp3", path_or_hf_repo="whisper-large-v3-turbo-german-f16-q4")
print(result)
```