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