transformers audio automatic-speech-recognition be license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- audio
- automatic-speech-recognition
language:
- be
pipeline_tag: automatic-speech-recognition
---
# Whisper small model for CTranslate2

This repository contains the conversion of fine-tunining Tiny version of Whisper 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/guillaumekln/faster-whisper).

## Install faster-whisper
```bash
pip install git+https://github.com/guillaumekln/faster-whisper.git
```

## Example

```python
from faster_whisper import WhisperModel

model = WhisperModel("bl4dylion/faster-whisper-tiny-belarusian")

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 <model_path> --output_dir faster-whisper-tiny-belarusian \
    --copy_files tokenizer_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).