Update app.py

app.py

@@ -275,7 +275,7 @@ igen_pubmed = gr.Interface(keyphrase_generator,
              title="PubMed Abstract Retriever", description="Generates the keyphrases from an article which best describes the article.",
              article= "This work is based on the paper <a href=https://dl.acm.org/doi/10.1145/3487664.3487701>provided here</a>." 
              "\t It uses the TextRank algorithm with SBERT to first find the top sentences and then extracts the keyphrases from those sentences using scispaCy and SBERT."
-             "\t The application then uses a <a href=https://arxiv.org/abs/2010.11784>UMLS based Bert model</a> to cluster the keyphrases using K-means clustering method and finally create a boolean query. After that the top 20 titles and abstracts are retrieved from PubMed database and displayed according to relevancy. "
+             "\t The application then uses a UMLS based BERT model, <a href=https://arxiv.org/abs/2010.11784>SapBERT</a> to cluster the keyphrases using K-means clustering method and finally create a boolean query. After that the top 20 titles and abstracts are retrieved from PubMed database and displayed according to relevancy. "
              "\t The list of SBERT models required in the textboxes can be found in <a href=www.sbert.net/docs/pretrained_models.html>SBERT Pre-trained models hub</a>."
              "\t The default model names are provided which can be changed from the list of pretrained models. "
              "\t The value of keyphrases can be changed. The default value is 10, minimum is 5 and a maximum value of 30.")