final?

app.py

@@ -6,11 +6,7 @@ from transformers import pipeline
 pipeline = pipeline("audio-classification", model="DanielDBGC/my_awesome_lang_class_mind_model")
 
 def predict(input_sound):
-    dataset = load_dataset("PolyAI/minds14", name="en-US", split="train")
-    dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
-    sampling_rate = dataset.features["audio"].sampling_rate
-    audio_file = dataset[0]["audio"]["path"]
-    predictions = pipeline(input_sound)
+    predictions = pipeline(input_sound[1])
     return {p["label"]: p["score"] for p in predictions} 
 
 gradio_app = gr.Interface(