Update app.py

app.py

@@ -29,12 +29,12 @@ css = '''
 maximum_concepts = 3
 
 #Pre download the files
-model_v1 = snapshot_download(repo_id="multimodalart/sd-fine-tunable")
-model_v2 = snapshot_download(repo_id="stabilityai/stable-diffusion-2")
-model_v2_512 = snapshot_download(repo_id="stabilityai/stable-diffusion-2-base")
-safety_checker = snapshot_download(repo_id="multimodalart/sd-sc")
-
-model_to_load = model_v1
+if(not is_shared_ui):
+    model_v1 = snapshot_download(repo_id="multimodalart/sd-fine-tunable")
+    model_v2 = snapshot_download(repo_id="stabilityai/stable-diffusion-2")
+    model_v2_512 = snapshot_download(repo_id="stabilityai/stable-diffusion-2-base")
+    safety_checker = snapshot_download(repo_id="multimodalart/sd-sc")
+    model_to_load = model_v1
 
 with zipfile.ZipFile("mix.zip", 'r') as zip_ref:
     zip_ref.extractall(".")
@@ -57,13 +57,14 @@ def swap_text(option, base):
         return [f"You are going to train a `style`, upload 10-20 images of the style you are planning on training on. You can use services like <a style='text-decoration: underline' href='https://www.birme.net/?target_width={resize_width}&target_height={resize_width}'>birme</a> for smart cropping. Name the files with the words you would like  {mandatory_liability}:", '''<img src="file/trsl_style.png" />''', f"You should name your concept with a unique made up word that has low chance of the model already knowing it (e.g.: `{instance_prompt_example}` here). Images will be automatically cropped to {resize_width}x{resize_width}", freeze_for, gr.update(visible=False)]
 
 def swap_base_model(selected_model):
-    global model_to_load
-    if(selected_model == "v1-5"):
-        model_to_load = model_v1
-    elif(selected_model == "v2-768"):
-        model_to_load = model_v2
-    else:
-        model_to_load = model_v2_512
+    if(not is_shared_ui):
+        global model_to_load
+        if(selected_model == "v1-5"):
+            model_to_load = model_v1
+        elif(selected_model == "v2-768"):
+            model_to_load = model_v2
+        else:
+            model_to_load = model_v2_512
 
 def count_files(*inputs):
     file_counter = 0