metadata
language:
- en
tags:
- audio
- automatic-speech-recognition
license: mit
library_name: ctranslate2
Whisper tiny.en model for CTranslate2
This repository contains the conversion of openai/whisper-tiny.en 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("tiny.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-tiny.en --output_dir faster-whisper-tiny.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.