Change typo and some sentences

app.py

@@ -321,10 +321,11 @@ Recent work using 🤖 **transformers** 🤖 on large text corpora has shown gre
 several different downstream NLP tasks. One such task is that of text summarization. The goal of text summarization 
 is to generate concise and accurate summaries from input document(s). There are 2 types of summarization:
 
- - **Extractive summarization** merely copies informative fragments from the input
- - **Abstractive summarization** may generate novel words. A good abstractive summary should cover principal 
-    information in the input and has to be linguistically fluent. This interactive blogpost will focus on this more difficult task of 
-    abstractive summary generation. Furthermore we will focus on factual errors in summaries, and less sentence fluency.""")
+ - **Extractive summarization** merely copies informative fragments from the input. 
+ - **Abstractive summarization** 
+ may generate novel words. A good abstractive summary should cover principal information in the input and has to be 
+ linguistically fluent. This interactive blogpost will focus on this more difficult task of abstractive summary 
+ generation. Furthermore we will focus mainly on hallucination errors, and less on sentence fluency.""")
 
 st.markdown("###")
 st.markdown("🤔 **Why is this important?** 🤔 Let's say we want to summarize news articles for a popular "