diff --git a/paddlenlp/transformers/llama/modeling_auto_pp.py b/paddlenlp/transformers/llama/modeling_auto_pp.py
index bc4fed315131..befdb5442eda 100644
--- a/paddlenlp/transformers/llama/modeling_auto_pp.py
+++ b/paddlenlp/transformers/llama/modeling_auto_pp.py
@@ -188,6 +188,11 @@ def manual_model_split(model, stage_idx, group, mode, pp_degree):
 
     layer_lists = model.layers
 
+    # shared_params_names only support ernie
+    shared_params_names = [["embedding_0.w_0.dist", "ernie_lm_head_0.w_0.dist"]]
+
+    shared_mp = build_shared_param_map(model, shared_params_names)
+
     def _build_stage(model, stage_idx, group):
         new_model = None
         if stage_idx == 0:  # 第一个model_chunk输入特殊处理
@@ -200,7 +205,7 @@ def _build_stage(model, stage_idx, group):
             new_model = LlamaChunk(
                 layer_lists[stage_idx * chunk_size : (stage_idx + 1) * chunk_size], is_first=False, is_last=False
             )
-        stage = PipelineStage(new_model, stage_idx, chunk_num, group=group)
+        stage = PipelineStage(new_model, stage_idx, chunk_num, group=group, shared_parameters=shared_mp)
         return stage
 
     stages = []
@@ -210,6 +215,25 @@ def _build_stage(model, stage_idx, group):
     return stages
 
 
+def build_shared_param_map(model, shared_params_names):
+    shared_mp = []
+    for pair in shared_params_names:
+        assert len(pair) == 2, "Only exactly two parameters are supported for sharing."
+        ori_name = pair[0]
+        sync_name = pair[1]
+        ori_param = get_param_from_name(ori_name, model)
+        sync_param = get_param_from_name(sync_name, model)
+        shared_mp.append({"params": [ori_param, sync_param]})
+    return shared_mp
+
+
+def get_param_from_name(param_name, model):
+    for param in model.parameters():
+        if param.name == param_name:
+            return param
+    raise ValueError(f"{param_name} not found in model parameters")
+
+
 def get_llama_pp_schedule(model, n_microbatches, loss_fn, mode, pp_degree, group):
     assert mode in ["VPP", "1F1B", "FThenB"]
     stages = manual_model_split(model, group.rank, group, mode, pp_degree)