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--- |
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language: |
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- dv |
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metrics: |
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- wer |
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- cer |
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pipeline_tag: automatic-speech-recognition |
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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 small-dv model for CTranslate2 |
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This repository contains the conversion of [whisper-small-dv](https://huggingface.co/davidggphy/whisper-small-dv) to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format. |
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The model is a finetuned version of openai/whisper-small to Divehi language using the [Common Voice 13 dataset](https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0) |
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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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# load from local folder |
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# model = WhisperModel("whisper-small-dv-ct2") |
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# load from the hub |
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model = WhisperModel("davidggphy/whisper-small-dv-ct2") |
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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 davidggphy/whisper-small-dv --output_dir whisper-small-dv-ct2 --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/davidggphy/whisper-small-dv).** |
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--- |
