Update README.md

README.md

@@ -12,4 +12,31 @@ library_name: ctranslate2
 
 # asadfgglie/faster-whisper-large-v3-zh-TW
 
-此模型是將[JacobLinCool/whisper-large-v3-turbo-common_voice_19_0-zh-TW](https://huggingface.co/JacobLinCool/whisper-large-v3-turbo-common_voice_19_0-zh-TW)轉換成`CTranslate2`格式的模型，可以在[faster-whisper](https://github.com/systran/faster-whisper)中使用。
+此模型是將[JacobLinCool/whisper-large-v3-turbo-common_voice_19_0-zh-TW](https://huggingface.co/JacobLinCool/whisper-large-v3-turbo-common_voice_19_0-zh-TW)
+轉換成`CTranslate2`格式的模型，可以在[faster-whisper](https://github.com/systran/faster-whisper)中使用。
+
+## Example
+
+```python
+from faster_whisper import WhisperModel
+
+model = WhisperModel("asadfgglie/faster-whisper-large-v3-zh-TW")
+
+segments, info = model.transcribe("audio.mp3")
+for segment in segments:
+    print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
+```
+
+## Conversion details
+
+原始模型是根據以下指令轉換:
+
+```
+ct2-transformers-converter --model JacobLinCool/whisper-large-v3-turbo-common_voice_19_0-zh-TW \
+ --output_dir whisper_model/faster-whisper-large-v3-zh-TW --copy_files preprocessor_config.json
+```
+
+在轉換完成後，請記得自行到原始模型的[model card](https://huggingface.co/openai/whisper-large-v3)中下載`tokenizer.json`。
+(因為`JacobLinCool/whisper-large-v3-turbo-common_voice_19_0-zh-TW`的repo中沒有，而`faster_whishper`又需要這個酷東東來做tokenizer)
+
+如果有需要，你可以在轉換指令中添加`--quantization float16`來指定量化精度。不過在推理時你依舊可以使用[`compute_type`](https://opennmt.net/CTranslate2/quantization.html)參數來進一步量化/去除量化。