Update README.md

README.md

@@ -67,9 +67,39 @@ model = AutoModelForCausalLM.from_pretrained(
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 
 # Generate answer
-prompt = "What is C. elegans?"
+prompt = """	
+Solve the following problem. Make sure to put the answer (and only answer) inside \boxed{}.
+
+Based on analysis of multinational aeromedical databases (e.g., EASA's EMPR, FAA's CAMI database, and military longitudinal studies), which statement accurately characterizes a fundamental limitation in definitively establishing cause-and-effect relationships for cardiovascular morbidity trends among commercial aircrew?
+
+A: Stratified sampling protocols universally eliminate survivorship bias
+B: Retroactive harmonization of biochemical markers across jurisdictions enables precise meta-analysis
+C: Inability to fully adjust for dominant confounding variables (e.g., socioeconomic status, undisclosed supplement use)
+D: Cohort studies consistently show declining age-adjusted myocardial infarction rates compared to the general population
+E: Mandatory polysomnography data provides complete correction for sleep disorder comorbidities
+F: Radiation dose metrics exhibit a linear correlation with arrhythmia incidence in jet aircraft pilots
+G: Genome-wide association studies have identified fully penetrant monogenic risk variants specific to aviators
+H: Continuous blood pressure monitoring during all flight phases yields statistically significant longitudinal datasets
+I: Pharmacokinetic interactions between hypoxia and statins are conclusively established in CRF models
+J: Regulatory divergence causes morbidity rates to universally decline across all regions after 2018"""
 input_ids = tokenizer.apply_chat_template(
-    [{"role": "user", "content": prompt}],
+    [{
+    "role":"system",
+    "content":""" 
+    You are a reasoning assistant.
+
+When solving problems:
+- Always place your reasoning inside think tags.
+- Think in structured steps, but keep it concise (3–4 short steps maximum).
+- Avoid repeating yourself or giving unnecessary background.
+- Use bullet points or brief numbered steps for clarity inside think tag.
+- After think end tag, provide only the final answer clearly and directly.
+- Do not include reasoning outside of the think tags.
+
+
+    """
+},
+        {"role": "user", "content": prompt}],
     add_generation_prompt=True,
     return_tensors="pt",
     tokenize=True,
@@ -81,7 +111,7 @@ output = model.generate(
     temperature=0.3,
     min_p=0.15,
     repetition_penalty=1.05,
-    max_new_tokens=512,
+    max_new_tokens=1024,
 )
 
 print(tokenizer.decode(output[0], skip_special_tokens=False))