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_basic_inference.py

@@ -1,10 +1,15 @@
 """基础推理测试 - 验证模型能否正常加载和生成"""
 import os
+import sys
 import glob
 import time
 import torch
 import psutil
-from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# 修复 Windows GBK 编码问题
+sys.stdout.reconfigure(encoding='utf-8', errors='replace')
+sys.stderr.reconfigure(encoding='utf-8', errors='replace')
 
 
 def get_model_path():
@@ -21,14 +26,6 @@ def test_basic_inference():
     print("Qwen3.5-9B 基础推理测试")
     print("=" * 60)
 
-    # 4-bit 量化配置 (RTX 3050 8GB 必须量化)
-    bnb_config = BitsAndBytesConfig(
-        load_in_4bit=True,
-        bnb_4bit_quant_type="nf4",
-        bnb_4bit_compute_dtype=torch.float16,
-        bnb_4bit_use_double_quant=True,
-    )
-
     model_path = get_model_path()
     print(f"\n模型路径: {model_path}")
 
@@ -38,13 +35,16 @@ def test_basic_inference():
     tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
     print(f"  Tokenizer 加载耗时: {time.time() - t0:.2f}s")
 
-    # 加载模型 (4-bit 量化)
-    print("加载模型 (4-bit 量化)...")
+    # 加载模型 (FP16 + GPU/CPU offload)
+    print("加载模型 (FP16 + CPU offload)...")
+    max_memory = {0: "6GiB", "cpu": "24GiB"}
     t0 = time.time()
     model = AutoModelForCausalLM.from_pretrained(
         model_path,
-        quantization_config=bnb_config,
+        torch_dtype=torch.float16,
         device_map="auto",
+        max_memory=max_memory,
+        offload_folder="vsp/qwen3.5-9b/offload",
         trust_remote_code=True,
     )
     load_time = time.time() - t0
@@ -80,7 +80,7 @@ def test_basic_inference():
         with torch.no_grad():
             outputs = model.generate(
                 **inputs,
-                max_new_tokens=256,
+                max_new_tokens=32,
                 do_sample=True,
                 temperature=0.7,
                 top_p=0.8,