app.py

import gradio as gr

learn = load_learner('cat_or_dog.pkl')

def predict(image):
    img = PILImage.create(image)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

gr.Interface(
    fn=predict, 
    inputs=gr.inputs.Image(shape=(512, 512)), 
    outputs=gr.outputs.Label(num_top_classes=3)
).launch(share=True)

demo.launch()