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davidggphy/whisper-small-dv-ct2
whisper-small-dv-ct2 is a automatic speech recognition model from davidggphy. Use it when you need speech turned into text. It is set up for ctranslate2. The card lists the license as mit.
This repository contains the conversion of whisper-small-dv to the CTranslate2 model format. The model is a finetuned version of openai/whisper-small to Divehi language using the Common Voice 13 dataset
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From the Hugging Face model README
This repository contains the conversion of whisper-small-dv to the CTranslate2 model format. The model is a finetuned version of openai/whisper-small to Divehi language using the Common Voice 13 dataset This model can be used in CTranslate2 or projects based on CTranslate2 such as faster-whisper.
from faster_whisper import WhisperModel
# load from local folder
# model = WhisperModel("whisper-small-dv-ct2")
# load from the hub
model = WhisperModel("davidggphy/whisper-small-dv-ct2")
segments, info = model.transcribe("audio.mp3")
for segment in segments:
print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
The original model was converted with the following command:
ct2-transformers-converter --model davidggphy/whisper-small-dv --output_dir whisper-small-dv-ct2 --copy_files tokenizer.json --quantization float16
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.