Sagicc's picture
- sr
- audio
- automatic-speech-recognition
license: mit
library_name: ctranslate2
# Whisper large-v3 Serbian fine-tunned model for CTranslate2
This repository contains the conversion of [Sagicc/whisper-large-v3-sr-combined]( 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("Sagicc/faster-whisper-large-v3-sr")
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-large-v3 --output_dir faster-whisper-large-v3 \
--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 fine-tunned model, see its [model card](**