app.py

import gradio as gr
from transformers import pipeline

pipe = pipeline(model="hackathon-pln-es/wav2vec2-base-finetuned-sentiment-mesd")

def classify_sentiment(audio):
  sentiment_classifier = pipe(audio)
  return sentiment_classifier


input_audio = gr.inputs.Audio(source="microphone", type="filepath", optional=True, label="Please record your voice")
label = gr.outputs.Label(num_top_classes=5)

gr.Interface(
    fn = classify_sentiment,
    inputs = input_audio,
    outputs = label,
    examples=[["images/cheetah1.jpg"], ["images/lion.jpg"]],
    theme="grass").launch()