diff --git a/modules/extras.py b/modules/extras.py
index 5e270250..7e222313 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -242,6 +242,9 @@ def run_pnginfo(image):
 
 
 def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
+    shared.state.begin()
+    shared.state.job = 'model-merge'
+
     def weighted_sum(theta0, theta1, alpha):
         return ((1 - alpha) * theta0) + (alpha * theta1)
 
@@ -263,8 +266,11 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
     theta_func1, theta_func2 = theta_funcs[interp_method]
 
     if theta_func1 and not tertiary_model_info:
+        shared.state.textinfo = "Failed: Interpolation method requires a tertiary model."
+        shared.state.end()
         return ["Failed: Interpolation method requires a tertiary model."] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
 
+    shared.state.textinfo = f"Loading {secondary_model_info.filename}..."
     print(f"Loading {secondary_model_info.filename}...")
     theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
 
@@ -281,6 +287,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
                     theta_1[key] = torch.zeros_like(theta_1[key])
         del theta_2
 
+    shared.state.textinfo = f"Loading {primary_model_info.filename}..."
     print(f"Loading {primary_model_info.filename}...")
     theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
 
@@ -291,6 +298,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
             a = theta_0[key]
             b = theta_1[key]
 
+            shared.state.textinfo = f'Merging layer {key}'
             # this enables merging an inpainting model (A) with another one (B);
             # where normal model would have 4 channels, for latenst space, inpainting model would
             # have another 4 channels for unmasked picture's latent space, plus one channel for mask, for a total of 9
@@ -303,8 +311,6 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
                 theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
                 result_is_inpainting_model = True
             else:
-                assert a.shape == b.shape, f'Incompatible shapes for layer {key}: A is {a.shape}, and B is {b.shape}'
-
                 theta_0[key] = theta_func2(a, b, multiplier)
 
             if save_as_half:
@@ -332,6 +338,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
 
     output_modelname = os.path.join(ckpt_dir, filename)
 
+    shared.state.textinfo = f"Saving to {output_modelname}..."
     print(f"Saving to {output_modelname}...")
 
     _, extension = os.path.splitext(output_modelname)
@@ -343,4 +350,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_nam
     sd_models.list_models()
 
     print("Checkpoint saved.")
+    shared.state.textinfo = "Checkpoint saved to " + output_modelname
+    shared.state.end()
+
     return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]