diff --git a/khaosz/model/transformer.py b/khaosz/model/transformer.py
index a557b86..f67edc9 100644
--- a/khaosz/model/transformer.py
+++ b/khaosz/model/transformer.py
@@ -71,10 +71,12 @@ class Transformer(nn.Module):
             DecoderBlock(config.n_dim, config.n_head, config.d_ffn, config.n_kvhead, config.norm_eps, layer_id)
             for layer_id in range(config.n_layer)
         ])
-        lm_head_init_weight = self.embed_tokens.weight if config.tie_weight == True else None
         
         self.norm = RMSNorm(config.n_dim, config.norm_eps)
-        self.lm_head = Linear(config.n_dim, config.vocab_size, weight_param=lm_head_init_weight)
+        self.lm_head = Linear(config.n_dim, config.vocab_size)
+        
+        if self.config.tie_weight == True:
+            self.lm_head.weight = self.embed_tokens.weight
 
         self._init_parameters()
     
diff --git a/tests/test_tie_weight.py b/tests/test_tie_weight.py
new file mode 100644
index 0000000..fbebd3e
--- /dev/null
+++ b/tests/test_tie_weight.py
@@ -0,0 +1,120 @@
+import os
+import json
+import torch
+import pytest
+import tempfile
+import safetensors.torch as st
+from khaosz.model.transformer import Transformer
+from khaosz.config.model_config import ModelConfig
+
+
+@pytest.fixture
+def transformer_test_env():
+    """创建Transformer测试专用环境"""
+    test_dir = tempfile.mkdtemp(prefix="transformer_test_")
+    config_path = os.path.join(test_dir, "config.json")
+    
+    # 测试配置参数
+    config = {
+        "vocab_size": 1000,
+        "n_dim": 128,
+        "n_head": 4,
+        "n_kvhead": 2,
+        "d_ffn": 256,
+        "m_len": 64,
+        "n_layer": 2,
+        "norm_eps": 1e-5
+    }
+    
+    with open(config_path, 'w') as f:
+        json.dump(config, f)
+    
+    yield {
+        "test_dir": test_dir,
+        "config_path": config_path,
+        "config": config
+    }
+    
+    if os.path.exists(test_dir):
+        try:
+            for file in os.listdir(test_dir):
+                os.remove(os.path.join(test_dir, file))
+            os.rmdir(test_dir)
+        except:
+            pass
+
+
+def test_tie_weight_shared_logic(transformer_test_env):
+
+    config_path = transformer_test_env["config_path"]
+    config_data = transformer_test_env["config"].copy()
+    config_data["tie_weight"] = True
+    
+    with open(config_path, 'w') as f:
+        json.dump(config_data, f)
+    
+    config = ModelConfig().load(config_path)
+    model = Transformer(config)
+    
+    assert torch.equal(model.lm_head.weight, model.embed_tokens.weight)
+    assert model.lm_head.weight.data_ptr() == model.embed_tokens.weight.data_ptr()
+    
+    original_weight = model.embed_tokens.weight.clone()
+    model.embed_tokens.weight.data[0, 0] = 100.0
+    
+    assert torch.equal(model.lm_head.weight, model.embed_tokens.weight)
+    assert not torch.equal(model.lm_head.weight, original_weight)
+    
+    config_data["tie_weight"] = False
+    
+    with open(config_path, 'w') as f:
+        json.dump(config_data, f)
+    
+    config = ModelConfig().load(config_path)
+    model = Transformer(config)
+    
+    assert not torch.equal(model.lm_head.weight, model.embed_tokens.weight)
+    assert model.lm_head.weight.data_ptr() != model.embed_tokens.weight.data_ptr()
+
+
+def test_model_save_load_with_tie_weight(transformer_test_env):
+    test_dir = transformer_test_env["test_dir"]
+    model_path = os.path.join(test_dir, "model.safetensors")
+    
+    config_data = transformer_test_env["config"].copy()
+    config_data["tie_weight"] = True
+    config_path = os.path.join(test_dir, "config.json")
+    
+    with open(config_path, 'w') as f:
+        json.dump(config_data, f)
+    
+    config = ModelConfig().load(config_path)
+    original_model = Transformer(config)
+    
+    st.save_file(original_model.state_dict(), model_path)
+
+    loaded_config = ModelConfig().load(config_path)
+    model = Transformer(loaded_config)
+    model.load_state_dict(st.load_file(model_path))
+    
+    assert torch.equal(model.lm_head.weight, model.embed_tokens.weight)
+    assert model.lm_head.weight.data_ptr() == model.embed_tokens.weight.data_ptr()
+    assert "lm_head.weight" not in model.state_dict()
+
+    config_data["tie_weight"] = False
+    with open(config_path, 'w') as f:
+        json.dump(config_data, f)
+    
+    config = ModelConfig().load(config_path)
+    original_model = Transformer(config)
+
+    st.save_file(original_model.state_dict(), model_path)
+    
+    loaded_config = ModelConfig().load(config_path)
+    model = Transformer(loaded_config)
+    model.load_state_dict(st.load_file(model_path))
+
+    assert not torch.equal(model.lm_head.weight, model.embed_tokens.weight)
+    assert model.lm_head.weight.data_ptr() != model.embed_tokens.weight.data_ptr()
+    assert "lm_head.weight" in model.state_dict()
+    
\ No newline at end of file