let's deploy to huggingface spaces

app.py

@@ -1,7 +1,18 @@
 import gradio as gr
+from fastai.vision.all import *
 
-def greet(name):
-    return "Hello " + name + "!!"
+learn = load_learner('model.pkl')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Is it a car or plance or bus?"
+description = "Are you a vampire sleeping for last 500 years and struggling to cope with this new world? Have you ever looked at something and could not figure out if it is a car or plane or bus? Don't worry you can now use this app to help you figure what it is exactly"
+examples = ['car.jpg', 'plane.jpg', 'bus.jpg']
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,examples=examples,interpretation=interpretation).launch()