Create app.py

add app.py python script with model loading + Gradio interface from my Kaggle for fastAI Lesson 2

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+# Load the model you trained and exported from Kaggle
+learn = load_learner("model.pkl")
+
+# Define a prediction function for Gradio
+def classify_image(img):
+    pred, idx, probs = learn.predict(img)
+    return {learn.dls.vocab[i]: float(probs[i]) for i in range(len(probs))}
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=classify_image,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label()
+)
+
+# Launch the interface when the app runs
+if __name__ == "__main__":
+    interface.launch()