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            ---
         
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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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            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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            there is also an [unquantized float16](https://huggingface.co/mlx-community/whisper-large-v3-turbo-german-f16) version
         
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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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            ```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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            # whisper-large-v3-turbo-german-f16-q4
         
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            This model was converted to MLX format.
         
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