Add more explanation

.ipynb_checkpoints/app-checkpoint.py

@@ -27,15 +27,13 @@ def infer(s1, s2):
         return data
 
 title = "Paraphrase Classification and Explanation"
-desc = "Classify and explain the semantic relationship between the two sentences"
-long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. It takes in two sentences as inputs. Feel free to modify the example inputs or enter in your own sentences."
+long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. The model takes in two sentences as inputs, and outputs a classification label and explanation. The model is trained on our Semantic Paraphrase Types dataset. Feel free to modify the example inputs or enter in your own sentences. Due to existing limitations, the explanation generated may not be entirely accurate. We hope that in future work, more powerful models can be trained and produce more accurate explanations."
 
 s1 = gr.Textbox(value="On Monday, Tom went to the market.",label="Sentence 1")
-s2 = gr.Textbox(value="Tom went to the market.",label="Sentence 2")
+s2 = gr.Textbox(value="Tom went to the market and bought a pig.",label="Sentence 2")
 
 demo = gr.Interface(fn=infer, inputs=[s1,s2], outputs="text",
                     title=title,
-                    description=desc,
                     article=long_desc,
                     )
 

app.py

@@ -27,15 +27,13 @@ def infer(s1, s2):
         return data
 
 title = "Paraphrase Classification and Explanation"
-desc = "Classify and explain the semantic relationship between the two sentences"
-long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. It takes in two sentences as inputs. Feel free to modify the example inputs or enter in your own sentences."
+long_desc = "This is a Flan-T5-Large model fine-tuned to perform paraphrase classification and explanation. The model takes in two sentences as inputs, and outputs a classification label and explanation. The model is trained on our Semantic Paraphrase Types dataset. Feel free to modify the example inputs or enter in your own sentences. Due to existing limitations, the explanation generated may not be entirely accurate. We hope that in future work, more powerful models can be trained and produce more accurate explanations."
 
 s1 = gr.Textbox(value="On Monday, Tom went to the market.",label="Sentence 1")
-s2 = gr.Textbox(value="Tom went to the market.",label="Sentence 2")
+s2 = gr.Textbox(value="Tom went to the market and bought a pig.",label="Sentence 2")
 
 demo = gr.Interface(fn=infer, inputs=[s1,s2], outputs="text",
                     title=title,
-                    description=desc,
                     article=long_desc,
                     )