Update app.py

app.py

@@ -44,11 +44,11 @@ def infer(
     generator = torch.Generator().manual_seed(seed)
     
     pipe = None
-    if (model_id=="stable-diffusion-v1-5/stable-diffusion-v1-5 with lora with text encoder"): 
+    if (model_id=="SD1.5 + lora Unet TextEncoder"): 
         pipe=DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch_dtype)
         pipe.unet = PeftModel.from_pretrained(pipe.unet,"um235/VanillaCat",subfolder="unet")
         pipe.text_encoder= PeftModel.from_pretrained(pipe.text_encoder,"um235/VanillaCat",subfolder="text_encoder")
-    elif  (model_id=="stable-diffusion-v1-5/stable-diffusion-v1-5 without lora with text encoder"): 
+    elif  (model_id=="SD1.5 + lora Unet"): 
         pipe=DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch_dtype)
         pipe.unet = PeftModel.from_pretrained(pipe.unet,"um235/cartoon_cat_stickers")
     else:
@@ -101,8 +101,8 @@ with gr.Blocks(css=css) as demo:
                 choices=[
                     "stable-diffusion-v1-5/stable-diffusion-v1-5",  
                     "CompVis/stable-diffusion-v1-4", 
-                    "stable-diffusion-v1-5/stable-diffusion-v1-5 with lora with text encoder",  
-                    "stable-diffusion-v1-5/stable-diffusion-v1-5 with lora without text encoder"
+                    "SD1.5 + lora Unet TextEncoder",  
+                    "SD1.5 + lora Unet"
                 ],
                 value="stable-diffusion-v1-5/stable-diffusion-v1-5 with lora with text encoder",  
                 show_label=True,