app.py

import gradio as gr
from transformers import pipeline
import torch

model_id = "ntu-spml/distilhubert"
device = 0 if torch.cuda.is_available() else -1
pipe = pipeline("audio-classification", model=model_id, device=device)

def classify_audio(filepath):
    import time
    start = time.time()
    preds = pipe(filepath)
    result = {p["label"]: round(p["score"], 3) for p in preds}
    return result, round(time.time() - start, 2)

gr.Interface(
    fn=classify_audio,
    inputs=gr.Audio(type="filepath", label="Upload Audio"),
    outputs=[gr.Label(label="Top Genres"), gr.Number(label="Time (s)")],
    title="🎵 Music Genre Classifier",
    description="Classifies the genre of uploaded audio using DistilHuBERT fine-tuned on GTZAN."
).launch()