Upload eval_gsm8k_vllm.py with huggingface_hub

eval_gsm8k_vllm.py

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+# /// script
+# requires-python = ">=3.10"
+# dependencies = [
+#     "datasets",
+#     "vllm>=0.4.0",
+#     "torch>=2.0.0",
+#     "transformers>=4.40.0",
+#     "huggingface-hub",
+# ]
+# ///
+
+import os
+import re
+from datasets import load_dataset
+
+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...")
+from vllm import LLM, SamplingParams
+from transformers import AutoTokenizer
+
+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}%")