Create app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+from transformers import pipeline
+
+pipe = pipeline("text-classification", model="lewtun/xlm-roberta-base-finetuned-marc-500-samples")
+
+def predict(text):
+  label2star = {"LABEL_0": "⭐", "LABEL_1": "⭐⭐", "LABEL_2": "⭐⭐⭐", "LABEL_3": "⭐⭐⭐⭐", "LABEL_4": "⭐⭐⭐⭐⭐"}
+  preds = pipe(text)[0]
+  return label2star[preds["label"]], round(preds["score"], 5)
+  
+  gradio_ui = gr.Interface(
+    fn=predict,
+    title="Review analysis",
+    description="Enter some review text about an Amazon product and check what the model predicts for it's star rating.",
+    inputs=[
+        gr.inputs.Textbox(lines=5, label="Paste some text here"),
+    ],
+    outputs=[
+        gr.outputs.Textbox(label="Label"),
+        gr.outputs.Textbox(label="Score"),
+    ],
+    examples=[
+        ["I love this book!", "The Hunger Games is the worst book ever"],
+    ],
+)
+
+gradio_ui.launch()