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app.py

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+from fastai.text.all import *
+import gradio as gr
+
+learn.load_learner('export.pkl')
+
+categories  = ('Negative', 'Positive')
+label = gr.outputs.Label()
+def classify(text):
+    pred,pred_idx,probs = learn.predict(text)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+
+intf = gr.Interface(fn=classify,inputs="text", outputs=label).launch(share=True)