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# requires-python = ">=3.10"
# dependencies = [
# "datasets",
# "vllm>=0.4.0",
# "torch>=2.0.0",
# "transformers>=4.40.0",
# "huggingface-hub",
# ]
# ///
import os
import re
def main():
from datasets import load_dataset
from vllm import LLM, SamplingParams
from transformers import AutoTokenizer
os.environ.setdefault("HF_HUB_TOKEN", os.getenv("HF_TOKEN", ""))
MODEL = os.getenv("MODEL", "Qwen/Qwen3.5-4B")
LIMIT = int(os.getenv("LIMIT", "250"))
print(f"Loading GSM8K dataset (limit={LIMIT})...")
ds = load_dataset("openai/gsm8k", "main", split="test").select(range(min(LIMIT, 1319)))
print(f"Loading model {MODEL} with vLLM...")
tok = AutoTokenizer.from_pretrained(MODEL, trust_remote_code=True)
llm = LLM(model=MODEL, trust_remote_code=True, dtype="half", gpu_memory_utilization=0.9)
sys_msg = "You are a helpful assistant that solves math problems step by step."
problems = []
answers = []
for ex in ds:
msgs = [
{"role": "system", "content": sys_msg},
{"role": "user", "content": f"Solve this math problem step by step. End your answer with 'ANSWER: <number>'\n\n{ex['question']}"},
]
formatted = tok.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
problems.append(formatted)
gt_match = re.search(r"####\s*(-?\d[\d,]*\.?\d*)", ex["answer"])
gt = gt_match.group(1).replace(",", "") if gt_match else ex["answer"].strip().split()[-1]
answers.append(gt)
print(f"Generating answers for {len(problems)} problems...")
sampling_params = SamplingParams(temperature=0.0, max_tokens=512, stop=["<|im_end|>", "<|endoftext|>"])
outputs = llm.generate(problems, sampling_params)
correct = 0
total = len(outputs)
for i, output in enumerate(outputs):
gen = output.outputs[0].text.strip()
pred_match = re.search(r"ANSWER:\s*(-?\d[\d,]*\.?\d*)", gen)
if pred_match:
pred = pred_match.group(1).replace(",", "")
else:
nums = re.findall(r"-?\d[\d,]*\.?\d*", gen)
pred = nums[-1].replace(",", "") if nums else ""
if pred == answers[i]:
correct += 1
if i < 5 or i % 50 == 0:
print(f"Q{i+1}: GT={answers[i]} Pred={pred} OK={pred==answers[i]}")
accuracy = correct / total * 100
print(f"\nGSM8K: {correct}/{total} = {accuracy:.2f}%")
if __name__ == "__main__":
main()
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