Create app.py

app.py

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+import gradio
+from transformers import pipeline
+
+username = "runaksh"
+repo_name = "finetuned-sentiment-model"
+repo_path = username+ '/' + repo_name
+sentiment_model = pipeline(model= repo_path)
+
+# Function for response generation
+def predict_sentiment(text):
+    result = sentiment_model(text)
+    if result[0]['label'].endswith('0'):
+        return 'Negative'
+    else:
+        return 'Positive'
+
+# Input from user
+in_prompt = gradio.components.Textbox(lines=10, placeholder=None, label='Enter review text')
+
+# Output response
+out_response = gradio.components.Textbox(type="text", label='Sentiment')
+
+# Gradio interface to generate UI link
+title = "Sentiment Classification"
+description = "Analyse sentiment of the given review"
+
+iface = gradio.Interface(fn = predict_sentiment,
+                         inputs = [in_prompt],
+                         outputs = [out_response],
+                         title = title,
+                         description = description)
+
+iface.launch(debug = True)#, server_name = "0.0.0.0", server_port = 8001) # Ref. for parameters: https://www.gradio.app/docs/interface