Update app.py

app.py

@@ -4,13 +4,13 @@ from transformers import pipeline
 import gradio as gr
 from gradio.mix import Parallel, Series
 
-io1 = gr.Interface.load('huggingface/google/pegasus-large')
-io2 = gr.Interface.load("huggingface/google/pegasus-cnn_dailymail")
-io3 = gr.Interface.load("huggingface/google/pegasus-xsum")
-io4 = gr.Interface.load('huggingface/google/pegasus-newsroom')
-io5 = gr.Interface.load("huggingface/google/pegasus-multi_news")
-io6 = gr.Interface.load("huggingface/google/pegasus-reddit_tifu")
-io7 = gr.Interface.load('huggingface/google/pegasus-arxiv')
+#io1 = gr.Interface.load('huggingface/google/pegasus-large')
+#io2 = gr.Interface.load("huggingface/google/pegasus-cnn_dailymail")
+#io3 = gr.Interface.load("huggingface/google/pegasus-xsum")
+#io4 = gr.Interface.load('huggingface/google/pegasus-newsroom')
+#io5 = gr.Interface.load("huggingface/google/pegasus-multi_news")
+#io6 = gr.Interface.load("huggingface/google/pegasus-reddit_tifu")
+#io7 = gr.Interface.load('huggingface/google/pegasus-arxiv')
 io8 = gr.Interface.load("huggingface/google/pegasus-pubmed")
 io9 = gr.Interface.load("huggingface/google/pegasus-wikihow")
 io10 = gr.Interface.load('huggingface/google/pegasus-gigaword')
@@ -79,6 +79,6 @@ iface = Parallel(io1,
                  title='Hugging Face Text Summarizer',
                  description=desc,
                  examples=sample,  # replace "sample" with directory to let gradio scan through those files and give you the text
-                 inputs=gr.inputs.Textbox(lines=10, label="Text"))
+                 inputs=gr.inputs.Textbox(lines=20, label="Text"))
 
 iface.launch(inline=False)