diff --git a/lora_gui.py b/lora_gui.py
index 4ca9d1c..ae703a2 100644
--- a/lora_gui.py
+++ b/lora_gui.py
@@ -46,6 +46,19 @@ folder_symbol = '\U0001f4c2'  # 📂
 refresh_symbol = '\U0001f504'  # 🔄
 save_style_symbol = '\U0001f4be'  # 💾
 document_symbol = '\U0001F4C4'   # 📄
+path_of_this_folder = os.getcwd()
+
+def getlocon(existance):
+    now_path = os.getcwd()
+    if existance:
+        print('Checking LoCon script version...')
+        os.chdir(os.path.join(path_of_this_folder, 'locon'))
+        os.system('git pull')
+        os.chdir(now_path)
+    else:
+        os.chdir(path_of_this_folder)
+        os.system('git clone https://github.com/KohakuBlueleaf/LoCon.git locon')
+        os.chdir(now_path)
 
 
 def save_configuration(
@@ -109,8 +122,8 @@ def save_configuration(
     caption_dropout_every_n_epochs,
     caption_dropout_rate,
     optimizer,
-    optimizer_args,
-    noise_offset,
+    optimizer_args,noise_offset, 
+    locon=0, conv_dim=0, conv_alpha=0,
 ):
     # Get list of function parameters and values
     parameters = list(locals().items())
@@ -217,8 +230,8 @@ def open_configuration(
     caption_dropout_every_n_epochs,
     caption_dropout_rate,
     optimizer,
-    optimizer_args,
-    noise_offset,
+    optimizer_args,noise_offset, 
+    locon=0, conv_dim=0, conv_alpha=0,
 ):
     # Get list of function parameters and values
     parameters = list(locals().items())
@@ -305,9 +318,9 @@ def train_model(
     caption_dropout_every_n_epochs,
     caption_dropout_rate,
     optimizer,
-    optimizer_args,
-    noise_offset,
-):
+    optimizer_args,noise_offset, 
+    locon, conv_dim, conv_alpha,
+):  
     if pretrained_model_name_or_path == '':
         msgbox('Source model information is missing')
         return
@@ -442,7 +455,12 @@ def train_model(
         run_cmd += f' --save_model_as={save_model_as}'
     if not float(prior_loss_weight) == 1.0:
         run_cmd += f' --prior_loss_weight={prior_loss_weight}'
-    run_cmd += f' --network_module=networks.lora'
+    if locon:
+        getlocon(os.path.exists(os.path.join(path_of_this_folder, 'locon')))
+        run_cmd += f' --network_module=locon.locon.locon_kohya'
+        run_cmd += f' --network_args "conv_dim={conv_dim}" "conv_alpha={conv_alpha}"'
+    else:
+        run_cmd += f' --network_module=networks.lora'
 
     if not (float(text_encoder_lr) == 0) or not (float(unet_lr) == 0):
         if not (float(text_encoder_lr) == 0) and not (float(unet_lr) == 0):
@@ -660,19 +678,19 @@ def lora_tab(
                 placeholder='Optional',
             )
             network_dim = gr.Slider(
-                minimum=4,
+                minimum=1,
                 maximum=1024,
                 label='Network Rank (Dimension)',
                 value=8,
-                step=4,
+                step=1,
                 interactive=True,
             )
             network_alpha = gr.Slider(
-                minimum=4,
+                minimum=1,
                 maximum=1024,
                 label='Network Alpha',
                 value=1,
-                step=4,
+                step=1,
                 interactive=True,
             )
         with gr.Row():
@@ -690,6 +708,22 @@ def lora_tab(
             )
             enable_bucket = gr.Checkbox(label='Enable buckets', value=True)
         with gr.Accordion('Advanced Configuration', open=False):
+            with gr.Row():
+                locon= gr.Checkbox(label='Train a LoCon instead of a general LoRA (does not support v2 base models) (may not be able to some utilities now)', value=False)
+                conv_dim = gr.Slider(
+                    minimum=1,
+                    maximum=512,
+                    value=1,
+                    step=1,
+                    label='LoCon Convolution Rank (Dimension)',
+                )
+                conv_alpha = gr.Slider(
+                    minimum=1,
+                    maximum=512,
+                    value=1,
+                    step=1,
+                    label='LoCon Convolution Alpha',
+                )
             with gr.Row():
                 no_token_padding = gr.Checkbox(
                     label='No token padding', value=False
@@ -834,8 +868,8 @@ def lora_tab(
         caption_dropout_every_n_epochs,
         caption_dropout_rate,
         optimizer,
-        optimizer_args,
-        noise_offset,
+        optimizer_args,noise_offset, 
+        locon, conv_dim, conv_alpha,
     ]
 
     button_open_config.click(