Update README.md

README.md

@@ -1,3 +1,41 @@
----
-license: mit
----
+---
+license: mit
+language:
+- ja
+base_model:
+- kotoba-tech/kotoba-whisper-v2.2
+pipeline_tag: automatic-speech-recognition
+---
+
+# Whisper kotoba-whisper-v2.2 model for CTranslate2
+This repository contains the conversion of [kotoba-tech/kotoba-whisper-v2.2](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.2) 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
+Install library and get a sample audio.
+```python
+pip install faster-whisper
+```
+
+Inference with the kotoba-whisper-v2.2-faster.
+```python
+from faster_whisper import WhisperModel
+
+if __name__ == '__main__':
+    model = WhisperModel(model_size_or_path="./kotoba-whisper-v2.2-faster", device="cuda", compute_type="float32", local_files_only=True)
+    segments, info = model.transcribe(audio="./123.wav", language="ja", chunk_length=5, condition_on_previous_text=False, hotwords="ノイミー")
+
+    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:
+```python
+ct2-transformers-converter --model kotoba-tech/kotoba-whisper-v2.2 --output_dir kotoba-whisper-v2.2-faster --copy_files tokenizer.json preprocessor_config.json --quantization float32
+```
+Note that the model weights are saved in FP32. 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 kotoba-whisper-v2.0, refer to the original [model card](https://huggingface.co/kotoba-tech/kotoba-whisper-v2.2).