Update README.md

README.md

@@ -64,7 +64,9 @@ compute_metrics(dataset["text"], transcriptions, languages=dataset["language"])
 By default, the dataset includes the audio, allowing you to run transcription directly.
 For example, the following code can be used to evaluate Whisper:
 ```python
-dataset = load_dataset("audioshake/jam-alt", revision="v1.0.0", decode_audio=False)["test"]
+dataset = load_dataset("audioshake/jam-alt", revision="v1.0.0")["test"]
+dataset = dataset.cast_column("audio", datasets.Audio(decode=False))  # Get the raw audio file, let Whisper decode it
+
 model = whisper.load_model("tiny")
 transcriptions = [
   "\n".join(s["text"].strip() for s in model.transcribe(a["path"])["segments"])