Update app.py

app.py

@@ -1,18 +1,13 @@
 import gradio as gr
-import transformers
-from transformers import BartTokenizer, BartForConditionalGeneration
 import spaces
+from transformers import pipeline
 
 model_name = 'Karzan/bart-summarization'
-tokenizer = BartTokenizer.from_pretrained(model_name)
-model = BartForConditionalGeneration.from_pretrained(model_name)
+summarizer = pipeline("summarization", model=model_name)
 
 @spaces.GPU(duration=120)
-def summarize(inp):
-    inp = inp.replace('\n','')
-    inp = tokenizer.encode(inp, return_tensors='pt', max_length=1024)
-    summary_ids = model.generate(inp, num_beams=4, max_length=150, early_stopping=True)
-    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+def summarize(text):
+    summary = summarizer(text, max_length=256, min_length=30, do_sample=False)[0]['summary_text']
     return summary
 
 gr.Interface(fn=summarize, inputs=gr.Textbox(lines=7, label="Input Text"), outputs="text").launch(inline=False)