Update README.md

README.md

@@ -32,7 +32,7 @@ wget https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml/resolve/main/gg
 
 ```bash
 wget https://huggingface.co/kotoba-tech/kotoba-whisper-v1.0-ggml/resolve/main/sample_ja_speech.wav
-make -j && ./main -m models/ggml-kotoba-whisper-v2.0.bin -f sample_ja_speech.wav --output-file transcription --output-json
+make -j && ./main -m models/ggml-kotoba-whisper-v2.0.bin -l ja -f sample_ja_speech.wav --output-file transcription --output-json
 ```
 
 Note that it runs only with 16-bit WAV files, so make sure to convert your input before running the tool. For example, you can use ffmpeg like this:
@@ -71,7 +71,7 @@ wget https://huggingface.co/kotoba-tech/kotoba-whisper-v2.0-ggml/resolve/main/gg
 
 Run inference on the sample audio:
 ```bash
-make -j && ./main -m models/ggml-kotoba-whisper-v2.0-q5_0.bin -f sample_ja_speech.wav --output-file transcription.quantized --output-json
+make -j && ./main -m models/ggml-kotoba-whisper-v2.0-q5_0.bin -l ja -f sample_ja_speech.wav --output-file transcription.quantized --output-json
 ```
 
 Note that the benchmark results are almost identical to the raw non-quantized model weight.