Update app.py

app.py

@@ -47,12 +47,15 @@ def infer(
     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.safety_checker = None
         pipe.text_encoder= PeftModel.from_pretrained(pipe.text_encoder,"um235/VanillaCat",subfolder="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.safety_checker = None
         pipe.unet = PeftModel.from_pretrained(pipe.unet,"um235/cartoon_cat_stickers")
     else:
         pipe=DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch_dtype)
+        pipe.safety_checker = None
     pipe = pipe.to(device)
 
     image = pipe(
@@ -104,7 +107,7 @@ with gr.Blocks(css=css) as demo:
                     "SD1.5 + lora Unet TextEncoder",  
                     "SD1.5 + lora Unet"
                 ],
-                value="stable-diffusion-v1-5/stable-diffusion-v1-5 with lora with text encoder",  
+                value="SD1.5 + lora Unet TextEncoder",  
                 show_label=True,
                 type="value",  
         )