Update app.py

app.py

@@ -2,15 +2,13 @@ import torch
 import gradio as gr
 from transformers import pipeline
 
-#text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
-de_text_summary = pipeline("summarization", model="Shahm/bart-german")
-#de_text_summary= pipeline("summarization", model="Joemgu/mlong-t5-large-sumstew")
+text_summary = pipeline("summarization", model="Falconsai/text_summarization", torch_dtype=torch.bfloat16)
 
 def summary (input):
     max_length = 1024  # adjust this value as needed
     if len(input) > max_length:
         input = input[:max_length]
-    output = de_text_summary(input)
+    output = text_summary(input)
     return output[0]['summary_text']
 
 gr.close_all()