Update app.py

app.py

@@ -13,16 +13,16 @@ pipeline = FluxPipeline.from_pretrained(
         torch_dtype=torch.bfloat16,
     ).to('cuda')
 
+pipeline.load_lora_weights("nicolaus-huang/PhotoDoodle", weight_name="pretrain.safetensors")
+pipeline.fuse_lora()
+pipeline.unload_lora_weights()
 
 @spaces.GPU
 def generate_image(image, prompt, guidance_scale, num_steps, lora_name):
     # Load the model
     
     # Load and fuse base LoRA weights
-    # pipeline.load_lora_weights("nicolaus-huang/PhotoDoodle", weight_name="pretrain.safetensors")
-    # pipeline.fuse_lora()
-    # pipeline.unload_lora_weights()
-
+    
     # Load selected LoRA effect if not using the pretrained base model
     pipeline.load_lora_weights("nicolaus-huang/PhotoDoodle", weight_name=f"{lora_name}.safetensors")
     pipeline.fuse_lora()