---
license: apache-2.0
language:
- ms
- en
tags:
- audio
- automatic-speech-recognition
- whisper
- ctranslate2
- faster-whisper
- malaysian
library_name: ctranslate2
base_model: mesolitica/Malaysian-whisper-large-v3-turbo-v3
---

# Malaysian Whisper Large v3 Turbo v3 model for CTranslate2

This repository contains the conversion of [mesolitica/Malaysian-whisper-large-v3-turbo-v3](https://huggingface.co/mesolitica/Malaysian-whisper-large-v3-turbo-v3) 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://github.com/systran/faster-whisper).

## Example

```python
from faster_whisper import WhisperModel

model = WhisperModel("SeamlessX/malaysian-faster-whisper-small-v3-ct2")

segments, info = model.transcribe("audio.mp3")
for segment in segments:
    print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
```

## Conversion Details

The original Transformers model was converted to the CTranslate2 format with the following command:

```bash
ct2-transformers-converter \
    --model mesolitica/Malaysian-whisper-large-v3-turbo-v3 \
    --output_dir malaysian-faster-whisper-large-v3-turbo-ct2 \
    --copy_files tokenizer.json preprocessor_config.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 original model, see its [model card](https://huggingface.co/mesolitica/Malaysian-whisper-large-v3-turbo-v3).**