diff --git a/extension/export_util/export_hf_model.py b/extension/export_util/export_hf_model.py
index e45ba8d417b..929773fa4d3 100644
--- a/extension/export_util/export_hf_model.py
+++ b/extension/export_util/export_hf_model.py
@@ -12,7 +12,7 @@
 from executorch.backends.xnnpack.partition.xnnpack_partitioner import XnnpackPartitioner
 from executorch.exir import EdgeCompileConfig, ExecutorchBackendConfig, to_edge
 from torch.nn.attention import SDPBackend
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoModelForCausalLM
 from transformers.generation.configuration_utils import GenerationConfig
 from transformers.integrations.executorch import convert_and_export_with_cache
 from transformers.modeling_utils import PreTrainedModel
@@ -73,12 +73,11 @@ def main() -> None:
     print(f"{model.config}")
     print(f"{model.generation_config}")
 
-    tokenizer = AutoTokenizer.from_pretrained(args.hf_model_repo)
-    input_ids = tokenizer([""], return_tensors="pt").to(device)["input_ids"]
+    input_ids = torch.tensor([[1]], dtype=torch.long)
     cache_position = torch.tensor([0], dtype=torch.long)
 
     def _get_constant_methods(model: PreTrainedModel):
-        return {
+        metadata = {
             "get_dtype": 5 if model.config.torch_dtype == torch.float16 else 6,
             "get_bos_id": model.config.bos_token_id,
             "get_eos_id": model.config.eos_token_id,
@@ -90,6 +89,7 @@ def _get_constant_methods(model: PreTrainedModel):
             "get_vocab_size": model.config.vocab_size,
             "use_kv_cache": model.generation_config.use_cache,
         }
+        return {k: v for k, v in metadata.items() if v is not None}
 
     with torch.nn.attention.sdpa_kernel([SDPBackend.MATH]), torch.no_grad():