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app.py

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+import gradio as gr
+from transformers import pipeline
+
+classifier = pipeline("text-classification", model="juliensimon/distilbert-amazon-shoe-reviews")
+
+def predict(review):
+        prediction = classifier(review)
+        print(prediction)
+        stars = prediction[0]['label']
+        stars = (int)(stars.split('_')[1])+1
+        score = 100*prediction[0]['score']
+        return "{} {:.0f}%".format("\U00002B50"*stars, score)
+
+iface = gr.Interface(fn=predict, inputs="text", outputs="text")
+iface.launch()

requirements.txt

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+torch
+transformers