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Sagicc/
faster-whisper-large-sr-v2

Name: faster-whisper-large-sr-v2
Availability: InStock

ctranslate2

audio

automatic-speech-recognition

mit

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Whisper large-v3 Serbian v2 fine-tunned model for CTranslate2

This repository contains the conversion of Sagicc/whisper-large-sr-v2 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("Sagicc/faster-whisper-large-sr-v2")
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 Sagicc/whisper-large-sr-v2 --output_dir faster-whisper-large-sr-v2 \
    --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.