Update README.md

README.md

@@ -29,11 +29,13 @@ model = AutoModelForCausalLM.from_pretrained(
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 instruction = "Please reason step by step, and put your final answer within \\boxed{}."
-prompt = f"{instruction}\nHow many r's are in the word \"strawberry\""
-# prompt = f"{instruction}\nThe arithmetic mean of 7, 2, $x$ and 10 is 9. What is the value of $x$?"
+# prompt = "How many r's are in the word \"strawberry\""
+# prompt = "The arithmetic mean of 7, 2, $x$ and 10 is 9. What is the value of $x$?"
+prompt = "Let $S$ be the set of points $(a,b)$ with $0 \le a,$ $b \le 1$ such that the equation \[x^4 + ax^3 - bx^2 + ax + 1 = 0\] has at least one real root.  Determine the area of the graph of $S.$"
+
 
 messages = [
-    {"role": "user", "content": prompt}
+    {"role": "user", "content": f"{instruction}\n{prompt}"},
 ]
 
 text = tokenizer.apply_chat_template(
@@ -46,7 +48,7 @@ model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
 
 generated_ids = model.generate(
     **model_inputs,
-    max_new_tokens=4096
+    max_new_tokens=16384
 )
 generated_ids = [
     output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
@@ -60,7 +62,6 @@ think_mode = ("<think>" in response)
 print(text+response)
 print(f"\nThink Mode: {think_mode}")
 print(f"Number of tokens: {num_tokens}")
-
 ```