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app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load audio classification pipeline
+classifier = pipeline("audio-classification", model="superb/wav2vec2-base-superb-ks")
+
+def classify_audio(audio):
+    # audio is (sample_rate, numpy array)
+    return classifier(audio)
+
+# Gradio UI
+demo = gr.Interface(
+    fn=classify_audio,
+    inputs=gr.Audio(type="filepath"),
+    outputs=gr.Label(num_top_classes=5),
+    title="Audio Classification",
+    description="Upload an audio file and classify the sound (e.g., speech, music, etc.)."
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+transformers
+torch
+torchaudio
+gradio