diff --git a/vllm/model_executor/models/llama.py b/vllm/model_executor/models/llama.py
index 5eddd3609e7f0..8454ceff98201 100644
--- a/vllm/model_executor/models/llama.py
+++ b/vllm/model_executor/models/llama.py
@@ -50,7 +50,7 @@
 from vllm.utils import is_hip, print_warning_once
 
 from .interfaces import SupportsLoRA
-from .utils import is_pp_missing_parameter, make_layers
+from .utils import is_pp_missing_parameter, make_layers, PPMissingLayer
 
 
 class LlamaMLP(nn.Module):
@@ -263,6 +263,8 @@ def __init__(
                 config.hidden_size,
                 org_num_embeddings=config.vocab_size,
             )
+        else:
+            self.embed_tokens = PPMissingLayer()
         self.start_layer, self.end_layer, self.layers = make_layers(
             config.num_hidden_layers,
             lambda: LlamaDecoderLayer(config=config,
@@ -271,7 +273,7 @@ def __init__(
         if get_pp_group().is_last_rank:
             self.norm = RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
         else:
-            self.norm = None
+            self.norm = PPMissingLayer()
 
     def get_input_embeddings(self, input_ids: torch.Tensor) -> torch.Tensor:
         return self.embed_tokens(input_ids)
@@ -386,9 +388,9 @@ def __init__(
                                                     config.vocab_size, logit_scale)
             self.sampler = Sampler()
         else:
-            self.lm_head = None
-            self.logits_processor = None
-            self.sampler = None
+            self.lm_head = PPMissingLayer()
+            self.logits_processor = PPMissingLayer()
+            self.sampler = PPMissingLayer()
 
     def forward(
         self,