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deepdml/faster-whisper-large-v3-turbo-ct2
faster-whisper-large-v3-turbo-ct2 is a automatic speech recognition model from deepdml. 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 deepdml/whisper-large-v3-turbo to the CTranslate2 model format.
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From the Hugging Face model README
This repository contains the conversion of deepdml/whisper-large-v3-turbo to the CTranslate2 model format.
This model can be used in CTranslate2 or projects based on CTranslate2 such as faster-whisper.
from faster_whisper import WhisperModel
model = WhisperModel("deepdml/faster-whisper-large-v3-turbo-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 deepdml/whisper-large-v3-turbo --output_dir faster-whisper-large-v3-turbo \
--copy_files tokenizer.json preprocessor_config.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.
For more information about the original model, see its model card.
Please cite the model using the following BibTeX entry:
@misc{deepdml/faster-whisper-large-v3-turbo-ct2,
title={Faster Whisper ct2 large-v3 turbo},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/faster-whisper-large-v3-turbo-ct2}},
year={2024}
}