Update app.py

app.py

@@ -9,8 +9,8 @@ model = T5ForConditionalGeneration.from_pretrained(model_name)
 # Define the summarization function
 def summarize_text(text):
     input_text = "summarize: " + text.strip()
-    input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
-    summary_ids = model.generate(input_ids, max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True)
+    input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=500, truncation=True)
+    summary_ids = model.generate(input_ids, max_length=140, min_length=40, length_penalty=2.0, num_beams=2, early_stopping=True)
     summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
     return summary