app.py

from transformers import pipeline
import gradio as gr

model_id = "Lightmourne/distilhubert-finetuned-gtzan"
pipe = pipeline("audio-classification", model=model_id)

def classify_audio(filepath):
    preds = pipe(filepath)
    outputs = {}
    for p in preds:
        outputs[p["label"]] = p["score"]
    return outputs


demo = gr.Blocks()

title = "Simple music genre classifier"
description = """
A simple music genre classifier allows you to categorize a music track into one of ten music genres, such as: "blues", "classical", "country", "disco", "hiphop", "jazz", "metal", "pop", "reggae", "rock". Link to the fine-tuned model checkpoint: https://huggingface.co/Lightmourne/distilhubert-finetuned-gtzan
"""

mic_classify_audio = gr.Interface(
    fn=classify_audio,
    inputs=gr.Audio(source="microphone", type="filepath"),
    outputs=gr.outputs.Label(),
    title=title,
    description=description,
)

file_classify_audio = gr.Interface(
    fn=classify_audio,
    inputs=gr.Audio(source="upload", type="filepath"),
    outputs=gr.outputs.Label(),
    #examples=[["./example.wav"]],
    title=title,
    description=description,
)

with demo:
    gr.TabbedInterface([mic_classify_audio, file_classify_audio], ["Microphone", "Audio File"])

demo.launch(debug=True)