Removed extra/unused code and modified description.

app.py

@@ -12,15 +12,6 @@ Original file is located at
 # !pip install gradio transformers==4.28.0 datasets
 
 import gradio as gr
-
-# def greet(name):
-#     return "Hello " + name
-
-
-# demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-
-# demo.launch()
-
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 from datasets import load_dataset
 import numpy as np
@@ -44,12 +35,8 @@ def summarize(text, temperature):
   title = tokenizer.decode(output[0], skip_special_tokens=True)
   return title
 
-sample = dataset['test']['abstract'][0]
-
-summarize(sample, 3.0)
-
 title = "Title Generator"
-description = """This model was trained to summarize text and generate a title.
+description = """This model was trained to generate a title given scientific paper abstracts.
 You can find more details about the fine-tuning of this BART model
 [here](https://huggingface.co/mehnaazasad/bart-large-finetuned-arxiv-co-ga-latest).
 While default parameter values are shown, feel free to experiment!