Edit model card

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.

Downloads last month
283,414
Inference Examples
Inference API (serverless) does not yet support ctranslate2 models for this pipeline type.

Spaces using deepdml/faster-whisper-large-v3-turbo-ct2 4