app.py

from transformers import pipeline

username = "afern24" ## Complete your username
model_id = f"{username}/distilhubert-finetuned-gtzan"
pipe = pipeline("audio-classification", model=model_id)

def classify_audio(filepath):
    """
    Goes from
    [{'score': 0.8339303731918335, 'label': 'country'},
  {'score': 0.11914275586605072, 'label': 'rock'},]

   to
   {"country":  0.8339303731918335, "rock":0.11914275586605072}
  """
    preds = pipe(filepath)
    outputs = {}
    for p in preds:
        outputs[p["label"]] = p["score"]
    return outputs

import gradio as gr

demo = gr.Interface(
    fn=classify_audio, inputs=gr.Audio(type="filepath"), outputs=[gr.Label(label="Predictions"), gr.Number(label="Prediction time (s)")], title="Distilhubert-finetuned-gtzan",
    description="Audio classifier based on music genres, for more check out my github ar www.github.com/Ferno22"
)
demo.launch(debug=True)