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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 |
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This model was converted to MLX format from primeline/whisper-large-v3-turbo-german |
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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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it is in float16, works well. quantized version: [4bit, float16](https://huggingface.co/mlx-community/whisper-large-v3-turbo-german-f16-q4) |
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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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``` |
