diff --git a/wan/any2video.py b/wan/any2video.py
index ba81250..67b1564 100644
--- a/wan/any2video.py
+++ b/wan/any2video.py
@@ -683,7 +683,7 @@ class WanAny2V:
         # init denoising
         updated_num_steps= len(timesteps)
         if callback != None:
-            from wgp import update_loras_slists
+            from wan.utils.utils import update_loras_slists
             update_loras_slists(self.model, loras_slists, updated_num_steps)
             callback(-1, None, True, override_num_inference_steps = updated_num_steps)
 
diff --git a/wan/diffusion_forcing.py b/wan/diffusion_forcing.py
index 9b5918a..85343fd 100644
--- a/wan/diffusion_forcing.py
+++ b/wan/diffusion_forcing.py
@@ -19,7 +19,7 @@ from wan.utils.utils import calculate_new_dimensions
 from .utils.fm_solvers import (FlowDPMSolverMultistepScheduler,
                                get_sampling_sigmas, retrieve_timesteps)
 from .utils.fm_solvers_unipc import FlowUniPCMultistepScheduler
-from wgp import update_loras_slists
+from wan.utils.utils import update_loras_slists
 
 class DTT2V:
 
diff --git a/wan/utils/utils.py b/wan/utils/utils.py
index fe0b6bf..9e61fcb 100644
--- a/wan/utils/utils.py
+++ b/wan/utils/utils.py
@@ -33,7 +33,13 @@ def seed_everything(seed: int):
         torch.cuda.manual_seed(seed)
     if torch.backends.mps.is_available():
         torch.mps.manual_seed(seed)
-        
+
+def update_loras_slists(trans, slists, num_inference_steps ):
+    from mmgp import offload
+    slists = [ expand_slist(slist, num_inference_steps ) if isinstance(slist, list) else slist for slist in slists ]
+    nos = [str(l) for l in range(len(slists))]
+    offload.activate_loras(trans, nos, slists ) 
+
 def resample(video_fps, video_frames_count, max_target_frames_count, target_fps, start_target_frame ):
     import math
 
diff --git a/wgp.py b/wgp.py
index 8e5335b..7888417 100644
--- a/wgp.py
+++ b/wgp.py
@@ -2107,8 +2107,9 @@ for file_path in models_def_paths:
     settings = json_def   
     existing_model_def = models_def.get(model_type, None) 
     if existing_model_def is not None:
-        existing_settings = models_def["settings"]
-        existing_settings.update(settings)
+        existing_settings = models_def.get("settings", None)
+        if existing_settings != None:
+            existing_settings.update(settings)
         existing_model_def.update(model_def)
     else:
         models_def[model_type] = model_def