app.py

from transformers import pipeline
import gradio as gr

pipe = pipeline(
    "audio-classification", model="juangtzi/wav2vec2-base-finetuned-gtzan"
)

def classify_audio(filepath):
    import time
    start_time = time.time()

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

    end_time = time.time()
    prediction_time = end_time - start_time


    return outputs, prediction_time


title = "🎵 Music Genre Classifier"
description = """
Music Genre Classifier model (Fine-tuned "facebook/wav2vec2-base") Dataset: [GTZAN](https://huggingface.co/datasets/marsyas/gtzan)
"""


demo = gr.Interface(
    fn=classify_audio,
    inputs=gr.Audio(type="filepath"),
    outputs=[gr.Label(), gr.Number(label="Prediction time (s)")],
    title=title,
    description=description,
    examples="./example",
    #cache_examples=True,
    allow_flagging="never",
)
demo.queue()

demo.launch(share=True)