update loading lora

app.py

@@ -29,11 +29,10 @@ sdxl_loras_raw = sorted(sdxl_loras_raw, key=lambda x: x["likes"], reverse=True)
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 model_id = "stabilityai/stable-diffusion-xl-base-1.0"
 
-if gr.NO_RELOAD:
-    pipe = DiffusionPipeline.from_pretrained(model_id, variant="fp16")
-    pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
-    pipe.load_lora_weights("jasperai/flash-sdxl", adapter_name="lora")
-    pipe.to(device=DEVICE, dtype=torch.float16)
+pipe = DiffusionPipeline.from_pretrained(model_id, variant="fp16")
+pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
+pipe.load_lora_weights("jasperai/flash-sdxl", adapter_name="lora")
+pipe.to(device=DEVICE, dtype=torch.float16)
 
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -43,7 +42,6 @@ MAX_IMAGE_SIZE = 1024
 def check_and_load_lora_user(user_lora_selector, user_lora_weight, gr_lora_loaded):
     flash_sdxl_id = "jasperai/flash-sdxl"
 
-    global pipe
     if user_lora_selector == "" or user_lora_selector == "":
         raise gr.Error("Please select a LoRA before running the inference.")