fix: 修复模型加载方式，改用 FP16+CPU offload

RTX 3050 8GB 无法完整加载 Qwen3.5-9B，即使量化也不行：
- bitsandbytes 4-bit 不支持 CPU offload
- bitsandbytes 8-bit 与 accelerate 存在版本兼容问题
- FP16 + CPU offload 可以加载但推理质量极差（输出乱码）
- 推理速度仅 0.4 tokens/s

结论：RTX 3050 8GB 不适合运行 Qwen3.5-9B

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

vsp/qwen3.5-9b/test_concurrency.py

@@ -1,35 +1,17 @@
 """并发压测 - 测试不同并发数下的性能表现"""
 import json
 import os
+import sys
 import glob
 import time
 import torch
 import threading
 from concurrent.futures import ThreadPoolExecutor, as_completed
-from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+from transformers import AutoModelForCausalLM, AutoTokenizer
 from datetime import datetime
 
-
-def load_model():
-    """加载 4-bit 量化模型"""
-    paths = glob.glob("vsp/qwen3.5-9b/model/**/config.json", recursive=True)
-    model_path = os.path.dirname(paths[0]) if paths else "Qwen/Qwen3.5-9B"
-
-    bnb_config = BitsAndBytesConfig(
-        load_in_4bit=True,
-        bnb_4bit_quant_type="nf4",
-        bnb_4bit_compute_dtype=torch.float16,
-        bnb_4bit_use_double_quant=True,
-    )
-
-    tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
-    model = AutoModelForCausalLM.from_pretrained(
-        model_path,
-        quantization_config=bnb_config,
-        device_map="auto",
-        trust_remote_code=True,
-    )
-    return model, tokenizer
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from model_utils import load_model
 
 
 def single_inference(model, tokenizer, prompt, lock, max_tokens=64):