Create app.py

app.py

@@ -0,0 +1,23 @@
+import os
+import gradio as gr
+from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
+
+HF_TOKEN = os.environ.get('HF_TOKEN')
+
+model_checkpoint = "besijar/dspa_review_classification"
+tokeniser = AutoTokenizer.from_pretrained(model_checkpoint, use_auth_token=HF_TOKEN)
+model = TFAutoModelForSequenceClassification.from_pretrained(model_checkpoint, use_auth_token=HF_TOKEN)
+
+example_review = "Tully's House Blend is the perfect K-Cup for me.  Sure, I occasionally enjoy the special flavors.....Mocha, Italian roast, French vanilla, but my favorite 'go-to'coffee is House Blend. Wakes me up in the morning with it's coffee house full hearty taste."
+
+def review_classify(review):
+    review = tokeniser.encode(review)
+    review = model.predict([review])
+    return int(review.logits.argmax())
+
+iface = gr.Interface(review_classify,
+                        title="Review Classification using DistilRoBERTa",
+                        inputs=[gr.Text(label="Review")],
+                        outputs=[gr.Number(label="Rating", precision=0)],
+                        examples=[example_review])
+iface.launch()