diff --git a/PixArt/model/blocks.py b/PixArt/model/blocks.py
index 19b76d2..d540d96 100644
--- a/PixArt/model/blocks.py
+++ b/PixArt/model/blocks.py
@@ -14,6 +14,7 @@
 import torch.nn.functional as F
 from einops import rearrange
 
+import comfy.ldm.common_dit
 from .utils import to_2tuple
 
 sdpa_32b = None
@@ -25,11 +26,14 @@
 
 from comfy import model_management
 if model_management.xformers_enabled():
-    import xformers
     import xformers.ops
+    if int((xformers.__version__).split(".")[2]) >= 28:
+        block_diagonal_mask_from_seqlens = xformers.ops.fmha.attn_bias.BlockDiagonalMask.from_seqlens
+    else:
+        block_diagonal_mask_from_seqlens = xformers.ops.fmha.BlockDiagonalMask.from_seqlens
 else:
     if model_management.xpu_available:
-        import intel_extension_for_pytorch as ipex
+        import intel_extension_for_pytorch as ipex # type: ignore
         import os
         if not torch.xpu.has_fp64_dtype() and not os.environ.get('IPEX_FORCE_ATTENTION_SLICE', None):
             from ...utils.IPEX.attention import scaled_dot_product_attention_32_bit
@@ -70,7 +74,7 @@ def forward(self, x, cond, mask=None):
         if model_management.xformers_enabled():
             attn_bias = None
             if mask is not None:
-                attn_bias = xformers.ops.fmha.BlockDiagonalMask.from_seqlens([N] * B, mask)
+                attn_bias = block_diagonal_mask_from_seqlens([N] * B, mask)
             x = xformers.ops.memory_efficient_attention(
                 q, k, v,
                 p=self.attn_drop.p,
diff --git a/Sana/models/sana_blocks.py b/Sana/models/sana_blocks.py
index 09ca72a..894b23c 100644
--- a/Sana/models/sana_blocks.py
+++ b/Sana/models/sana_blocks.py
@@ -39,8 +39,11 @@
 
 from comfy import model_management
 if model_management.xformers_enabled():
-    import xformers
     import xformers.ops
+    if int((xformers.__version__).split(".")[2]) >= 28:
+        block_diagonal_mask_from_seqlens = xformers.ops.fmha.attn_bias.BlockDiagonalMask.from_seqlens
+    else:
+        block_diagonal_mask_from_seqlens = xformers.ops.fmha.BlockDiagonalMask.from_seqlens
 else:
     if model_management.xpu_available:
         import intel_extension_for_pytorch as ipex # type: ignore
@@ -94,7 +97,7 @@ def forward(self, x, cond, mask=None):
         if model_management.xformers_enabled():
             attn_bias = None
             if mask is not None:
-                attn_bias = xformers.ops.fmha.BlockDiagonalMask.from_seqlens([N] * B, mask)
+                attn_bias = block_diagonal_mask_from_seqlens([N] * B, mask)
             x = xformers.ops.memory_efficient_attention(
                 q, k, v,
                 p=self.attn_drop.p,