Create README.md

README.md

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+---
+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).