Update app.py

app.py

@@ -25,7 +25,7 @@ model = AutoModelForCausalLM.from_pretrained(
 
 checkpoint = "gregorlied/Llama-3.2-1B-Instruct-Medical-Report-Summarization"
 model = PeftModel.from_pretrained(model, checkpoint)
-model = model.merge_and_unload()
+# model = model.merge_and_unload()
 
 class Person(BaseModel):
   life_style: str
@@ -116,7 +116,7 @@ def summarize(text):
     ]
     
     response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
-    return response[0]
+    return response
 
 with gr.Blocks() as demo:
     gr.Markdown("## 📝 Structured Information Extraction for Clinical Reports")