# Whisper medium-v2 Serbian fine-tunned model for CTranslate2

This repository contains the conversion of [Sagicc/whisper-medium-sr-v2](https://huggingface.co/Sagicc/whisper-medium-sr-v2) to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format.

This model can be used in CTranslate2 or projects based on CTranslate2 such as [faster-whisper](https://huggingface.co/Sagicc/whisper-medium-sr-v2).

## Example

```python
from faster_whisper import WhisperModel
model = WhisperModel("Sagicc/faster-whisper-medium-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-medium-sr-v2 --output_dir faster-whisper-medium-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](https://opennmt.net/CTranslate2/quantization.html).

## More information

**For more information about the fine-tunned model, see its [model card](https://huggingface.co/Sagicc/whisper-medium-sr-v2).**
{"language": ["sr"], "license": "mit", "library_name": "ctranslate2", "tags": ["audio", "automatic-speech-recognition"]}
ctranslate2 audio automatic-speech-recognition sr license:mit region:us