diff --git a/devtools/backend_debug/__init__.py b/devtools/backend_debug/__init__.py
index b457b7d11d5..56975e80713 100644
--- a/devtools/backend_debug/__init__.py
+++ b/devtools/backend_debug/__init__.py
@@ -7,6 +7,7 @@
 from executorch.devtools.backend_debug.delegation_info import (
     DelegationBreakdown,
     get_delegation_info,
+    print_delegation_info,
 )
 
-__all__ = ["DelegationBreakdown", "get_delegation_info"]
+__all__ = ["DelegationBreakdown", "get_delegation_info", "print_delegation_info"]
diff --git a/devtools/backend_debug/delegation_info.py b/devtools/backend_debug/delegation_info.py
index b237d162f7a..41c7f8d8e7d 100644
--- a/devtools/backend_debug/delegation_info.py
+++ b/devtools/backend_debug/delegation_info.py
@@ -11,7 +11,7 @@
 
 import pandas as pd
 import torch
-
+from tabulate import tabulate
 
 # Column names of the DataFrame returned by DelegationInfo.get_operator_delegation_dataframe()
 # which describes the summarized delegation information grouped by each operator type
@@ -174,3 +174,10 @@ def _insert_op_occurrences_dict(node_name: str, delegated: bool) -> None:
         num_delegated_subgraphs=delegated_subgraph_counter,
         delegation_by_operator=op_occurrences_dict,
     )
+
+
+def print_delegation_info(graph_module: torch.fx.GraphModule):
+    delegation_info = get_delegation_info(graph_module)
+    print(delegation_info.get_summary())
+    df = delegation_info.get_operator_delegation_dataframe()
+    print(tabulate(df, headers="keys", tablefmt="fancy_grid"))
diff --git a/examples/models/llama/export_llama_lib.py b/examples/models/llama/export_llama_lib.py
index 618c74e8706..4ad92903534 100644
--- a/examples/models/llama/export_llama_lib.py
+++ b/examples/models/llama/export_llama_lib.py
@@ -23,7 +23,7 @@
 import torch
 
 from executorch.backends.vulkan._passes.remove_asserts import remove_asserts
-from executorch.devtools.backend_debug import get_delegation_info
+from executorch.devtools.backend_debug import print_delegation_info
 
 from executorch.devtools.etrecord import generate_etrecord
 from executorch.exir.passes.init_mutable_pass import InitializedMutableBufferPass
@@ -46,7 +46,6 @@
     get_vulkan_quantizer,
 )
 from executorch.util.activation_memory_profiler import generate_memory_trace
-from tabulate import tabulate
 
 from ..model_factory import EagerModelFactory
 from .source_transformation.apply_spin_quant_r1_r2 import (
@@ -801,12 +800,6 @@ def _export_llama(args) -> LLMEdgeManager:  # noqa: C901
     for partitioner in partitioners:
         logging.info(f"--> {partitioner.__class__.__name__}")
 
-    def print_delegation_info(graph_module: torch.fx.GraphModule):
-        delegation_info = get_delegation_info(graph_module)
-        print(delegation_info.get_summary())
-        df = delegation_info.get_operator_delegation_dataframe()
-        print(tabulate(df, headers="keys", tablefmt="fancy_grid"))
-
     additional_passes = []
     if args.model in TORCHTUNE_DEFINED_MODELS:
         additional_passes = [InitializedMutableBufferPass(["kv_cache_pos"])]