faster-whisper-large-v3-turbo

Note: this model is a copy of dropbox-dash/faster-whisper-large-v3-turbo and is not a product of pyannoteAI. Please refer to the original version for support.

Whisper large-v3 turbo model for CTranslate2

This repository contains the conversion of openai/whisper-large-v3-turbo to the CTranslate2 model format.

This model can be used in CTranslate2 or projects based on CTranslate2 models such as faster-whisper. It is called automatically for Mobius Labs fork of faster-whisper.

Example

from faster_whisper import WhisperModel

model = WhisperModel("dropbox-dash/faster-whisper-large-v3-turbo")

segments, info = model.transcribe("audio.mp3")
for segment in segments:
    print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))

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.

Conversion details

The openAI model was converted with the following command:

ct2-transformers-converter --model openai/whisper-large-v3-turbo --output_dir faster-whisper-large-v3-turbo \
    --copy_files tokenizer.json preprocessor_config.json --quantization float16

More Information

For more information about the original model, see its model card.