added model

app.py

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+import gradio as gr
+import gr.themes.*
+
+# import model for gradio
+learn_gradio = load_learner('image_classifier_flowers.pkl')
+
+# build prediction function
+labels = learn_gradio.dls.vocab
+
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn_gradio.predict(img)
+    return {str(labels[i]): float(probs[i]) for i in range(len(labels))}
+
+# build gradio interface
+gradio_interface = gr.Interface(
+    theme=gr.themes.Soft(),
+    title = "Flower Image Classifier",
+    description = "A simple classifier for the 102-category <a href='https://www.robots.ox.ac.uk/~vgg/data/flowers/' target='new'>Flower Dataset</a>",
+    fn=predict, 
+    inputs = gr.inputs.Image(shape=(224,224)), 
+    outputs = gr.outputs.Label(num_top_classes=5),
+    enable_queue=True,
+)
+
+# launch interface
+gradio_interface.launch(share=True)

image_classifier_flowers.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5d08b9b787bb49daf960feeefe9ca861698b32087218b8717580265e95ba7abf
+size 87704526

requirements.txt

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+fastai