diff --git a/colossalai/builder/pipeline.py b/colossalai/builder/pipeline.py
index a25e8990d..3d14ce23e 100644
--- a/colossalai/builder/pipeline.py
+++ b/colossalai/builder/pipeline.py
@@ -240,7 +240,6 @@ def build_pipeline_model_from_cfg(config,
 def build_pipeline_model(layers: nn.Sequential, num_chunks: int = 1, verbose: bool = False):
     """An intializer to split the model into different stages for pipeline parallelism.
     Note that `layer` must be `torch.nn.Sequential`.
-
     Args:
         layers (`torch.nn.Sequential`): Layers of model
         num_chunks: The number of chunks you want to have on the current stage. This value should be 1
@@ -252,7 +251,9 @@ def build_pipeline_model(layers: nn.Sequential, num_chunks: int = 1, verbose: bo
     partitions = partition_uniform(len(layers), pipeline_parallel_size, num_chunks)
     module_list = []
     for start, end in partitions[pipeline_rank]:
-        module_list.append(nn.Sequential(*layers[start:end]))
+        module_list.append(nn.Sequential(*[nn.Identity() for _ in range(start)],
+                                         *layers[start:end],
+                                         *[nn.Identity() for _ in range(len(layers) - end)]))
     if verbose:
         logger = get_dist_logger()
         logger.info(f'Total {len(layers)} layers', ranks=[0])
@@ -263,3 +264,4 @@ def build_pipeline_model(layers: nn.Sequential, num_chunks: int = 1, verbose: bo
                 log_str += '\n'.join([str(layer) for layer in layers[start:end]]) + '\n'
             logger.info(log_str, ranks=[0])
     return nn.ModuleList(module_list) if len(module_list) > 1 else module_list[0]
+    
\ No newline at end of file
diff --git a/colossalai/initialize.py b/colossalai/initialize.py
index 08bd43f62..bdbc96681 100644
--- a/colossalai/initialize.py
+++ b/colossalai/initialize.py
@@ -399,6 +399,8 @@ def initialize(model: nn.Module,
         else:
             scatter_gather = False
         if use_interleaved:
+            if isinstance(model, nn.Sequential):
+                model = nn.ModuleList([model])
             schedule = InterleavedPipelineSchedule(gpc.config.NUM_MICRO_BATCHES,
                                                    gpc.config.model.num_chunks,
                                                    tensor_shape=tensor_shape,
@@ -434,7 +436,6 @@ def initialize(model: nn.Module,
             accumulate_size=grad_accum_size,
             gradient_handlers=gradient_handlers,
             lr_scheduler=lr_scheduler)
-
     engine = Engine(model=model,
                     optimizer=optimizer,
                     criterion=criterion,