Update README.md

README.md

@@ -26,9 +26,9 @@ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model.to(device)
 
-def generate_answer(question, context, max_length=64):
+def generate_answer(question, context, max_length=512):
     input_text = f"question: {question} context: {context}"
-    inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True, padding="max_length").to(device)
+    inputs = tokenizer(input_text, return_tensors="pt", max_length=max_length, truncation=True, padding="max_length").to(device)
     
     outputs = model.generate(
         **inputs,