diff --git a/python/llm/src/ipex_llm/transformers/models/stablelm.py b/python/llm/src/ipex_llm/transformers/models/stablelm.py
index 00845966..bfcb50ec 100644
--- a/python/llm/src/ipex_llm/transformers/models/stablelm.py
+++ b/python/llm/src/ipex_llm/transformers/models/stablelm.py
@@ -141,34 +141,24 @@ def stablelm_attention_forward(
         kv_seq_len += past_key_value.get_usable_length(kv_seq_len, self.layer_idx)
 
     # Partial rotary embedding
-    query_rot, query_pass = (
-        query_states[..., : self.rotary_emb.dim],
-        query_states[..., self.rotary_emb.dim:],
-    )
-    key_rot, key_pass = (
-        key_states[..., : self.rotary_emb.dim],
-        key_states[..., self.rotary_emb.dim:],
-    )
-    cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
-    # [batch_size, num_heads, seq_length, head_dim // config.partial_rotary_factor]
+    # [batch_size, num_heads, seq_length, head_dim * config.partial_rotary_factor]
+    rot_dim = self.rotary_emb.dim
     if should_use_fuse_rope(hidden_states, position_ids, self.training):
-        query_rot, key_rot = apply_rotary_pos_emb_cache_freq_xpu(query_rot,
-                                                                 key_rot,
-                                                                 sin,
-                                                                 cos,
-                                                                 "stablelm",
-                                                                 position_ids)
+        import xe_addons
+        xe_addons.rotary_half_inplaced(self.rotary_emb.inv_freq, position_ids,
+                                       query_states[..., :rot_dim], key_states[..., :rot_dim])
     else:
+        query_rot, query_pass = query_states[..., :rot_dim], query_states[..., rot_dim:]
+        key_rot, key_pass = key_states[..., :rot_dim], key_states[..., rot_dim:]
+        cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len)
         query_rot, key_rot = apply_rotary_pos_emb(query_rot,
                                                   key_rot,
                                                   cos,
                                                   sin,
                                                   position_ids,
                                                   "stablelm")
-
-    # [batch_size, num_heads, seq_length, head_dim]
-    query_states = torch.cat((query_rot, query_pass), dim=-1)
-    key_states = torch.cat((key_rot, key_pass), dim=-1)
+        query_states = torch.cat((query_rot, query_pass), dim=-1)
+        key_states = torch.cat((key_rot, key_pass), dim=-1)
 
     key_states, value_states = past_key_value.update(key_states, value_states,
                                                      self.layer_idx, None)