diff --git a/python/llm/src/ipex_llm/transformers/models/baichuan.py b/python/llm/src/ipex_llm/transformers/models/baichuan.py
index 9d4688df..21d86b06 100644
--- a/python/llm/src/ipex_llm/transformers/models/baichuan.py
+++ b/python/llm/src/ipex_llm/transformers/models/baichuan.py
@@ -89,9 +89,11 @@ def baichuan_model_7b_forward(
         output_hidden_states: Optional[bool] = None,
         return_dict: Optional[bool] = None,
 ) -> Union[Tuple, BaseModelOutputWithPast]:
-    output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions
+    output_attentions = output_attentions if output_attentions is not None \
+        else self.config.output_attentions
     output_hidden_states = (
-        output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
+        output_hidden_states if output_hidden_states is not None else
+        self.config.output_hidden_states
     )
     use_cache = use_cache if use_cache is not None else self.config.use_cache
 
@@ -110,7 +112,8 @@ def baichuan_model_7b_forward(
 
     # retrieve input_ids and inputs_embeds
     if input_ids is not None and inputs_embeds is not None:
-        raise ValueError("You cannot specify both decoder_input_ids and decoder_inputs_embeds at the same time")
+        raise ValueError("You cannot specify both decoder_input_ids and decoder_inputs_embeds at \
+                          the same time")
     elif input_ids is not None:
         batch_size, seq_length = input_ids.shape
     elif inputs_embeds is not None:
@@ -130,9 +133,8 @@ def baichuan_model_7b_forward(
 
     if position_ids is None:
         device = input_ids.device if input_ids is not None else inputs_embeds.device
-        position_ids = torch.arange(
-            past_key_values_length, seq_length + past_key_values_length, dtype=torch.long, device=device
-        )
+        position_ids = torch.arange(past_key_values_length, seq_length + past_key_values_length,
+                                    dtype=torch.long, device=device)
         position_ids = position_ids.unsqueeze(0).view(-1, seq_length)
     else:
         position_ids = position_ids.view(-1, seq_length).long()
@@ -216,7 +218,8 @@ def baichuan_model_7b_forward(
 
     next_cache = next_decoder_cache if use_cache else None
     if not return_dict:
-        return tuple(v for v in [hidden_states, next_cache, all_hidden_states, all_self_attns] if v is not None)
+        return tuple(v for v in [hidden_states, next_cache, all_hidden_states, all_self_attns]
+                     if v is not None)
     return BaseModelOutputWithPast(
         last_hidden_state=hidden_states,
         past_key_values=next_cache,