diff --git a/src/diffusers/models/transformers/transformer_skyreels_v2.py b/src/diffusers/models/transformers/transformer_skyreels_v2.py
index b17e30ce2717..1503aacc05dc 100644
--- a/src/diffusers/models/transformers/transformer_skyreels_v2.py
+++ b/src/diffusers/models/transformers/transformer_skyreels_v2.py
@@ -64,8 +64,25 @@ def __init__(
         self.linear = nn.Linear(embedding_dim, output_dim)
         self.linear.weight.data[:embedding_dim, :] = torch.eye(embedding_dim)
         self.linear.weight.data[embedding_dim:, :] = torch.eye(embedding_dim)
+        # Initialize bias to match the original scale_shift_table initialization pattern
+        self.linear.bias.data = torch.randn(output_dim) / embedding_dim**0.5
         self.norm = FP32LayerNorm(embedding_dim, norm_eps, norm_elementwise_affine)
 
+    def load_from_scale_shift_table(self, scale_shift_table: torch.Tensor) -> None:
+        """
+        Helper method to transfer scale_shift_table values from old model checkpoints.
+        This can be used to migrate models saved with the old format to the new AdaLayerNorm format.
+        
+        Args:
+            scale_shift_table: Tensor of shape (1, 2, embedding_dim) from old model format
+        """
+        if scale_shift_table.shape[0] != 1 or scale_shift_table.shape[1] != 2:
+            raise ValueError(f"Expected scale_shift_table shape (1, 2, embedding_dim), got {scale_shift_table.shape}")
+        
+        with torch.no_grad():
+            # Flatten the scale_shift_table to match the bias shape
+            self.linear.bias.data = scale_shift_table.view(-1)
+
     def forward(self, x: torch.Tensor, temb: torch.Tensor) -> torch.Tensor:
         if temb.ndim == 2:
             # If temb is 2D, we assume it has 1-D time embedding values for each batch.
@@ -443,7 +460,7 @@ class SkyReelsV2Transformer3DModel(ModelMixin, ConfigMixin, PeftAdapterMixin, Fr
     _supports_gradient_checkpointing = True
     _skip_layerwise_casting_patterns = ["patch_embedding", "condition_embedder", "norm"]
     _no_split_modules = ["SkyReelsV2TransformerBlock", "SkyReelsV2AdaLayerNorm"]
-    _keep_in_fp32_modules = ["time_embedder", "scale_shift_table", "norm1", "norm2", "norm3"]
+    _keep_in_fp32_modules = ["time_embedder", "norm1", "norm2", "norm3", "norm_out"]
     _keys_to_ignore_on_load_unexpected = ["norm_added_q", "scale_shift_table"]
     _keys_to_ignore_on_load_missing = ["norm_out.linear.weight", "norm_out.linear.bias"]