app.py

from transformers import pipeline
import gradio as gr 
model = pipeline("image-classification", model="microsoft/swin-tiny-patch4-window7-224")

def classify_image(image):    
    predictions = model(image)    
    return {pred["label"]: pred["score"] for pred in predictions}

title = "Mi primer Demo"
description = "Test con Hugging Face y Gradio"
demo = gr.Interface(fn=classify_image,inputs=gr.Image(type="pil", label="Selecciona la imagen"),
                    outputs=gr.Label(num_top_classes=5), 
                    title=title,
                    description=description,) 
demo.launch()