diff --git a/engines/python/setup/djl_python/transformers_neuronx_scheduler/optimum_neuron_scheduler.py b/engines/python/setup/djl_python/transformers_neuronx_scheduler/optimum_neuron_scheduler.py
index d75a0600b..b53f9ce07 100644
--- a/engines/python/setup/djl_python/transformers_neuronx_scheduler/optimum_neuron_scheduler.py
+++ b/engines/python/setup/djl_python/transformers_neuronx_scheduler/optimum_neuron_scheduler.py
@@ -190,6 +190,15 @@ def increment_cache_id(self):
     def trim_cache_id(self):
         self._cache_id = self._cache_id.max()
 
+    def is_slot_eos_token(self, token) -> bool:
+        if hasattr(self._generation_config, "eos_token_id"):
+            if isinstance(self._generation_config.eos_token_id, int):
+                return token == self._generation_config.eos_token_id
+            else:
+                return token in self._generation_config.eos_token_id
+        else:
+            return False
+
     @property
     def stopped(self) -> bool:
         return self._selector.stopping_criteria(self._tokens, None)
@@ -381,7 +390,9 @@ def _generate_token(
             slot.append(next_token, next_token_text)
             generated_text = None
             finish_reason = None
-            if next_token == self.tokenizer.eos_token_id:
+            if slot.is_slot_eos_token(next_token):
+                finish_reason = FinishReason.FINISH_REASON_EOS_TOKEN
+            elif next_token == self.tokenizer.eos_token_id:
                 finish_reason = FinishReason.FINISH_REASON_EOS_TOKEN
             elif slot.stopped:
                 finish_reason = FinishReason.FINISH_REASON_LENGTH
@@ -403,7 +414,8 @@ def _generate_token(
                     token_id=next_token,
                     token_logprob=next_log_prob,
                     token_text=next_token_text,
-                    token_is_special=(next_token in [self.special_tokens]),
+                    token_is_special=(next_token in [self.special_tokens])
+                    or (finish_reason == FinishReason.FINISH_REASON_EOS_TOKEN),
                     generated_text=generated_text,
                 ))
         return generations
diff --git a/engines/python/setup/djl_python/transformers_neuronx_scheduler/token_selector.py b/engines/python/setup/djl_python/transformers_neuronx_scheduler/token_selector.py
index b94149b74..612866b08 100644
--- a/engines/python/setup/djl_python/transformers_neuronx_scheduler/token_selector.py
+++ b/engines/python/setup/djl_python/transformers_neuronx_scheduler/token_selector.py
@@ -13,7 +13,7 @@
 # The below code is heavily inspired from Optimum Neuron under the following link:
 # https://github.com/huggingface/optimum-neuron/blob/974f34336bb36b1b64890c191c558a1575372be7/optimum/neuron/generation/token_selector.py
 import logging
-from typing import Optional
+from typing import Optional, Union, List
 import torch
 from transformers.generation import (
     GenerationConfig,
@@ -63,7 +63,7 @@ def __init__(
         mode: GenerationMode,
         logits_processor: LogitsProcessorList,
         stopping_criteria: StoppingCriteriaList,
-        eos_token_id: int,
+        eos_token_id: Union[List[int], int],
         pad_token_id: int,
         logits_warper: Optional[LogitsProcessorList] = None,
     ):
@@ -139,9 +139,9 @@ def create(cls, input_ids: torch.Tensor,
         # The generation requires special tokens
         eos_token_id = generation_config.eos_token_id
         # This is not supposed to happen for any of the models we support
-        assert eos_token_id is not None and not isinstance(eos_token_id, list)
         if generation_config.pad_token_id is None:
-            generation_config.pad_token_id = eos_token_id
+            generation_config.pad_token_id = eos_token_id if isinstance(
+                eos_token_id, int) else eos_token_id[0]
 
         generation_mode = model._get_generation_mode(generation_config, None)
         if generation_mode not in [