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VOLKL/
faster-whisper-medium.en

Name: faster-whisper-medium.en
Availability: InStock

ctranslate2

audio

automatic-speech-recognition

mit

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Whisper medium.en model for CTranslate2

This repository contains the conversion of openai/whisper-medium.en to the CTranslate2 model format.

This model can be used in CTranslate2 or projects based on CTranslate2 such as faster-whisper.

Example

python

from faster_whisper import WhisperModel

model = WhisperModel("medium.en")

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.en --output_dir faster-whisper-medium.en \
    --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.

VOLKL/faster-whisper-medium.en

Whisper medium.en model for CTranslate2

Example

Conversion details

More information

VOLKL/
faster-whisper-medium.en