changing the model, input examples and label

app.py

@@ -2,19 +2,19 @@ import gradio as gr
 from transformers import pipeline
 
 def generate_story(story):
-    ner = pipeline("ner", model="dbmdz/bert-large-cased-finetuned-conll03-english")
+    ner = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions")
     return str(ner(story))
 
 demo = gr.Interface (
     fn=generate_story,
-    description="Named Entity Recognition Demo with BERT (dbmdz/bert-large-cased-finetuned-conll03-english)",
+    description="Sentiment analysis multi-class with (SamLowe/roberta-base-go_emotions",
     examples=[
-        ["England won the 2019 world cup vs The 2019 world cup happened in England."],
-        ["Washington is the capital of the US vs The first president of the US was Washington."],
-        ["My name is Ganesh Kamath and I work at AMD in Bangalore."]
+        ["I am looking forward to a good maths session."],
+        ["Good that they broke up, not like it was going anywhere anyways."],
+        ["I am going to punch through his face next time he mentions notes!"]
     ],
     inputs=[gr.Textbox(lines=7, label="Text")],
-    outputs=[gr.Textbox(lines=7, label="Story NER")]
+    outputs=[gr.Textbox(lines=7, label="Multiclass Sentiment Analysis")]
 )
 
 demo.launch(share=True)