diff --git a/deepmd/pt/model/atomic_model/linear_atomic_model.py b/deepmd/pt/model/atomic_model/linear_atomic_model.py
index 5c1db5a550..6cede6a265 100644
--- a/deepmd/pt/model/atomic_model/linear_atomic_model.py
+++ b/deepmd/pt/model/atomic_model/linear_atomic_model.py
@@ -199,9 +199,9 @@ def forward_atomic(
                 mapping,
                 fparam,
                 aparam,
-            )["energy"]
+            )
             # apply bias to each individual model
-            ener_list.append(model.apply_out_stat(raw_ret, mapping[extended_atype]))
+            ener_list.append(model.apply_out_stat(raw_ret, mapping[extended_atype][:,:nloc])["energy"])
         weights = self._compute_weight(extended_coord, extended_atype, nlists_)
 
         fit_ret = {
diff --git a/deepmd/pt/model/model/make_model.py b/deepmd/pt/model/model/make_model.py
index f1a0334335..ab3f3d0a8f 100644
--- a/deepmd/pt/model/model/make_model.py
+++ b/deepmd/pt/model/model/make_model.py
@@ -172,6 +172,10 @@ def forward_common(
             model_predict = self.output_type_cast(model_predict, input_prec)
             return model_predict
 
+        @property
+        def out_bias(self)-> torch.Tensor:
+            return self.atomic_model.out_bias
+
         def change_out_bias(
             self,
             merged,