app.py

import gradio as gr
from fastai.vision.all import *

categories = ('Dog', 'Cat')
learn = load_learner('model1.pk1')
def classify_image(img):
    pred , idx , probs = learn.predict(img)
    return dict(zip(categories , map(float,probs)))



image = gr.inputs.image(shape=(192 ,192))
label = gr.outputs.Label()
examples = ['dog.jpg', 'cat.jpg', 'dumo.jpg']
demo = gr.Interface(fn=classify_image, inputs=image, outputs= label)
demo.launch(inline = False)

m = learn.model
ps = list(m.parameters())

ps[1]