diff --git a/modules/extras.py b/modules/extras.py
index a9788e7dec668b534f0151438ee425323a4ffde0..158732048ae01eeb01c98cdeacf9b81272044fc7 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -4,6 +4,7 @@ import numpy as np
 from PIL import Image
 
 import torch
+import tqdm
 
 from modules import processing, shared, images, devices
 from modules.shared import opts
@@ -149,28 +150,45 @@ def run_modelmerger(modelname_0, modelname_1, interp_method, interp_amount):
         alpha = alpha * alpha * (3 - (2 * alpha))
         return theta0 + ((theta1 - theta0) * alpha)
 
-    model_0 = torch.load('models/' + modelname_0 + '.ckpt')
-    model_1 = torch.load('models/' + modelname_1 + '.ckpt')
+    if os.path.exists(modelname_0):
+        model0_filename = modelname_0
+        modelname_0 = os.path.splitext(os.path.basename(modelname_0))[0]
+    else:
+        model0_filename = 'models/' + modelname_0 + '.ckpt'
+
+    if os.path.exists(modelname_1):
+        model1_filename = modelname_1
+        modelname_1 = os.path.splitext(os.path.basename(modelname_1))[0]
+    else:
+        model1_filename = 'models/' + modelname_1 + '.ckpt'
+
+    print(f"Loading {model0_filename}...")
+    model_0 = torch.load(model0_filename, map_location='cpu')
+
+    print(f"Loading {model1_filename}...")
+    model_1 = torch.load(model1_filename, map_location='cpu')
     
     theta_0 = model_0['state_dict']
     theta_1 = model_1['state_dict']
-    theta_func = weighted_sum
-    
-    if interp_method == "Weighted Sum":
-        theta_func = weighted_sum
-    if interp_method == "Sigmoid":
-        theta_func = sigmoid
-    
-    for key in theta_0.keys():
+
+    theta_funcs = {
+        "Weighted Sum": weighted_sum,
+        "Sigmoid": sigmoid,
+    }
+    theta_func = theta_funcs[interp_method]
+
+    print(f"Merging...")
+    for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
             theta_0[key] = theta_func(theta_0[key], theta_1[key], interp_amount)
     
     for key in theta_1.keys():
         if 'model' in key and key not in theta_0:
             theta_0[key] = theta_1[key]
-    
-    output_modelname = 'models/' + modelname_0 + '-' + modelname_1 + '-merged.ckpt';
-    
+
+    output_modelname = 'models/' + modelname_0 + '-' + modelname_1 + '-merged.ckpt'
+    print(f"Saving to {output_modelname}...")
     torch.save(model_0, output_modelname)
-    
-    return "<p>Model saved to " + output_modelname + "</p>"
+
+    print(f"Checkpoint saved.")
+    return "Checkpoint saved to " + output_modelname
diff --git a/modules/ui.py b/modules/ui.py
index 5476c32fc297e3e0f004e99945016d17e4712153..e96109c9c59a1bcbd2ba68ddc2342bf9741d3a6b 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -49,6 +49,7 @@ sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
 
 css_hide_progressbar = """
 .wrap .m-12 svg { display:none!important; }
+.wrap .m-12::before { content:"Loading..." }
 .progress-bar { display:none!important; }
 .meta-text { display:none!important; }
 """
@@ -865,7 +866,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
                 submit = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')
             
             with gr.Column(variant='panel'):
-                submit_result = gr.HTML(elem_id="modelmerger_result")
+                submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)
 
             submit.click(
                 fn=run_modelmerger,