---

language:

• 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 tags:
• audio
• automatic-speech-recognition license: mit library_name: ctranslate2

---

Whisper small model for CTranslate2

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

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-small --output_dir faster-whisper-small \
    --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.