language	tags	license	library_name
en zh de es ru ko fr ja pt tr pl ca nl ar sv it id hi fi vi he uk el ms cs ro da hu ta no th ur hr bg lt la mi ml cy sk te fa lv bn sr az sl kn et mk br eu is hy ne mn bs kk sq sw gl mr pa si km sn yo so af oc ka be tg sd gu am yi lo uz fo ht ps tk nn mt sa lb my bo tl mg as tt haw ln ha ba jw su	audio automatic-speech-recognition	mit	ctranslate2

Whisper medium model for CTranslate2

This repository contains the conversion of openai/whisper-medium 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("medium")

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 openai/whisper-medium --output_dir faster-whisper-medium \
    --copy_files tokenizer.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.