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language: |
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- en |
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- zh |
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- de |
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- es |
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- ru |
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- ko |
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- fr |
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- ja |
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- tr |
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- pl |
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- ca |
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- nl |
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- ar |
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- sv |
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- it |
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- id |
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- hi |
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- fi |
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- vi |
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- he |
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- uk |
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- el |
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- ms |
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- cs |
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- ro |
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- da |
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- hu |
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- ta |
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- 'no' |
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- az |
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- sl |
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- kn |
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- mk |
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- br |
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- eu |
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- is |
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- hy |
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- sq |
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- yo |
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- so |
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- af |
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- oc |
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- be |
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- tg |
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- sd |
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- gu |
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- am |
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- yi |
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- lo |
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- uz |
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- fo |
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- lb |
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- my |
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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 large-v2 model for CTranslate2 |
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This repository contains the conversion of [openai/whisper-large-v2](https://huggingface.co./openai/whisper-large-v2) 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/guillaumekln/faster-whisper). |
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## Example |
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```python |
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from faster_whisper import WhisperModel |
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model = WhisperModel("large-v2") |
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segments, info = model.transcribe("audio.mp3") |
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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 openai/whisper-large-v2 --output_dir faster-whisper-large-v2 \ |
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--copy_files tokenizer.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./openai/whisper-large-v2).** |
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