Update modeling_llama.py

updating LlamaRotaryEmbedding based on transformers==4.49

modeling_llama.py

@@ -189,27 +189,7 @@ class LlamaAttention(nn.Module):
         self._init_rope()
 
     def _init_rope(self):
-        if self.config.rope_scaling is None:
-            self.rotary_emb = LlamaRotaryEmbedding(self.config)
-        else:
-            scaling_type = self.config.rope_scaling["type"]
-            scaling_factor = self.config.rope_scaling["factor"]
-            if scaling_type == "linear":
-                self.rotary_emb = LlamaLinearScalingRotaryEmbedding(
-                    self.head_dim,
-                    max_position_embeddings=self.max_position_embeddings,
-                    scaling_factor=scaling_factor,
-                    base=self.rope_theta,
-                )
-            elif scaling_type == "dynamic":
-                self.rotary_emb = LlamaDynamicNTKScalingRotaryEmbedding(
-                    self.head_dim,
-                    max_position_embeddings=self.max_position_embeddings,
-                    scaling_factor=scaling_factor,
-                    base=self.rope_theta,
-                )
-            else:
-                raise ValueError(f"Unknown RoPE scaling type {scaling_type}")
+        self.rotary_emb = LlamaRotaryEmbedding(self.config)
 
     def forward(
         self,