Whisper large-v3 turbo model for CTranslate2
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.
Example
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))
Conversion details
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.
More information
For more information about the original model, see its model card.
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Inference API (serverless) does not yet support ctranslate2 models for this pipeline type.