diff --git a/comfy/ldm/lightricks/model.py b/comfy/ldm/lightricks/model.py
index 87ed0995..f49cef95 100644
--- a/comfy/ldm/lightricks/model.py
+++ b/comfy/ldm/lightricks/model.py
@@ -415,13 +415,15 @@ class LTXVModel(torch.nn.Module):
 
         self.patchifier = SymmetricPatchifier(1)
 
-    def forward(self, x, timestep, context, attention_mask, frame_rate=25, guiding_latent=None, **kwargs):
+    def forward(self, x, timestep, context, attention_mask, frame_rate=25, guiding_latent=None, transformer_options={}, **kwargs):
+        patches_replace = transformer_options.get("patches_replace", {})
+
         indices_grid = self.patchifier.get_grid(
             orig_num_frames=x.shape[2],
             orig_height=x.shape[3],
             orig_width=x.shape[4],
             batch_size=x.shape[0],
-            scale_grid=((1 / frame_rate) * 8, 32, 32), #TODO: controlable frame rate
+            scale_grid=((1 / frame_rate) * 8, 32, 32),
             device=x.device,
         )
 
@@ -468,14 +470,24 @@ class LTXVModel(torch.nn.Module):
                 batch_size, -1, x.shape[-1]
             )
 
-        for block in self.transformer_blocks:
-            x = block(
-                x,
-                context=context,
-                attention_mask=attention_mask,
-                timestep=timestep,
-                pe=pe
-            )
+        blocks_replace = patches_replace.get("dit", {})
+        for i, block in enumerate(self.transformer_blocks):
+            if ("double_block", i) in blocks_replace:
+                def block_wrap(args):
+                    out = {}
+                    out["img"] = block(args["img"], context=args["txt"], attention_mask=args["attention_mask"], timestep=args["vec"], pe=args["pe"])
+                    return out
+
+                out = blocks_replace[("double_block", i)]({"img": x, "txt": context, "attention_mask": attention_mask, "vec": timestep, "pe": pe}, {"original_block": block_wrap})
+                x = out["img"]
+            else:
+                x = block(
+                    x,
+                    context=context,
+                    attention_mask=attention_mask,
+                    timestep=timestep,
+                    pe=pe
+                )
 
         # 3. Output
         scale_shift_values = (