Update app.py

app.py

@@ -166,11 +166,8 @@ def run_lora(prompt, negative, lora_scale, selected_state, sdxl_loras, sdxl_lora
     loaded_state_dict = copy.deepcopy(state_dicts[repo_name]["state_dict"])
     cross_attention_kwargs = None
     if last_lora != repo_name:
-        #if(last_fused):
-            #pipe.unfuse_lora()
         pipe.load_lora_weights(loaded_state_dict, adapter_name=sdxl_loras[selected_state.index]["repo"])
         pipe.set_adapters([sdxl_loras[selected_state.index]["repo"], "lcm_lora"], adapter_weights=[0.8, 1.0])
-        #last_fused = True
         is_pivotal = sdxl_loras[selected_state.index]["is_pivotal"]
         if(is_pivotal):
             #Add the textual inversion embeddings from pivotal tuning models