---
language:
  - hu
tags:
  - audio
  - automatic-speech-recognition
datasets:
- mozilla-foundation/common_voice_16_0
base_model: openai/whisper-tiny
license: mit
library_name: ctranslate2
---

# Whisper tiny model for CTranslate2

This repository contains the conversion of a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format. Fine-tune is made by [@sarpba](https://huggingface.co/sarpba)  on the Common Voice 16 dataset of Mozilla Foundation.

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("tiny")

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 Hungarians/whisper-tiny-cv16-hu-v2 --output_dir faster-whisper-tiny-cv16-v2-fp16.hu \
    --quantization fp16 --low_cpu_mem_usage --copy_files tokenizer_config.json preprocessor_config.json
```

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).

## HASH calculation

Hash calculation is executed with md5hash in the directory of the model with:

```
find ./ -maxdepth 1 -type f -not -path '*/\.*'  -exec md5sum {} \; | tr -d ' '| jq -R 'split("./") | {(.[1]): (.[0])}' | jq -s 'add' > hash.json
```

## More information

**For more information about the original model, see its [model card](https://huggingface.co/Hungarians/whisper-tiny-cv16-hu-v2).**