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aTrain-core/faster-whisper-large-v3-turbo
faster-whisper-large-v3-turbo is a automatic speech recognition model from aTrain-core. 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("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.