Update README.md

README.md

@@ -42,13 +42,14 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16)
 
 event = 'The Magna Carta'
-prompt = f"Q: Craft a compelling first-person historical narrative that captures the significance of {event} and the essence of its era. Think step by step about the key events, historical accuracy, stylistic prose, emotions, and sensory details that define the period."
+prompt = f"Q: Craft a compelling first-person historical narrative that captures the significance of {event} and the essence of its era. Think step by step about the key events, historical accuracy, stylistic prose, emotions, and sensory details that define the period.\nA: "
 
 inputs = tokenizer.encode(prompt, return_tensors = 'pt').to(model.device)
 output = model.generate(inputs, max_new_tokens = 750, pad_token_id = tokenizer.pad_token_id, do_sample = True)
 
 generated_text = tokenizer.decode(output[0], skip_special_tokens = True)
-print(generated_text)```
+print(generated_text)
+```
 
 **Prompt Format** <br />
 My prompt is formatted to have the model build a first-person narrative based upon a certain event or era. The narrative should be engaging, accurate, and include prose and vivid details from the era to be entertaining and informative to the reader.