Update app.py

app.py

@@ -2,9 +2,6 @@ import torch
 from transformers import BartTokenizer, BartForConditionalGeneration
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelWithLMHead, TranslationPipeline
-
-
-
 from transformers import pipeline
 
 pipe= pipeline('text2text-generation', model="SEBIS/legal_t5_small_trans_fr_en")
@@ -16,11 +13,6 @@ def generate_text(inp):
     return result
 #Gradio Interface
 
-
-
-
-
-
 model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
 tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
 
@@ -38,6 +30,6 @@ def article_summarization(result):
 
 #iface = gr.Interface(fn=article_summarization,title="Summarization in English",description="facebook/bart-large-cnn for summarization in English", inputs=(lines=50,['text']), outputs=["text"])
 
-iface = gr.Interface(fn=article_summarization,title="Summarization in English",description="facebook/bart-large-cnn for summarization in English", inputs=gr.inputs.Textbox(lines=50, placeholder="Enter newpaper article to be summarized"), outputs=["result"])
+iface = gr.Interface(fn=article_summarization,title="Summarization in English",description="facebook/bart-large-cnn for summarization in English", inputs=gr.inputs.Textbox(lines=50, placeholder="Enter newspaper article to be summarized"))
 
 iface.launch()