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--- |
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language: ja |
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tags: |
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- audio |
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- automatic-speech-recognition |
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license: mit |
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library_name: ctranslate2 |
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--- |
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# Whisper kotoba-whisper-v1.0 model for CTranslate2 |
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This repository contains the conversion of [kotoba-tech/kotoba-whisper-v1.0](https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0) to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format. |
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This model can be used in CTranslate2 or projects based on CTranslate2 such as [faster-whisper](https://github.com/systran/faster-whisper). |
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## Example |
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Install library and download sample audio. |
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```shell |
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pip install faster-whisper |
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wget https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml/resolve/main/sample_ja_speech.wav |
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``` |
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Inference with the kotoba-whisper-v1.0-faster. |
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```python |
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from faster_whisper import WhisperModel |
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model = WhisperModel("kotoba-tech/kotoba-whisper-v1.0-faster") |
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segments, info = model.transcribe("sample_ja_speech.wav", language="ja", chunk_length=15, condition_on_previous_text=False) |
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for segment in segments: |
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print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text)) |
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``` |
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## Conversion details |
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The original model was converted with the following command: |
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``` |
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ct2-transformers-converter --model kotoba-tech/kotoba-whisper-v1.0 --output_dir kotoba-whisper-v1.0-faster \ |
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--copy_files tokenizer.json preprocessor_config.json --quantization float16 |
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``` |
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Note that the model weights are saved in FP16. This type can be changed when the model is loaded using the [`compute_type` option in CTranslate2](https://opennmt.net/CTranslate2/quantization.html). |
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## More information |
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**For more information about the original model, see its [model card](https://huggingface.co/distil-whisper/distil-large-v2).** |
