Update app.py

app.py

@@ -37,7 +37,7 @@ base_model = "black-forest-labs/FLUX.1-dev"
 
 # load pipe
 
-txt2img_pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype)
+txt2img_pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype，low_cpu_mem_usage=False)
 
 txt2img_pipe = txt2img_pipe.to(device)
 txt2img_pipe.__class__.load_lora_into_transformer = classmethod(load_lora_into_transformer)
@@ -156,7 +156,7 @@ def run_lora(prompt, image_url, lora_strings_json, image_strength,  cfg_scale, s
                     adapter_weights.append(adapter_weight)
                     if lora_repo and weights and adapter_name:
                         try:
-                            txt2img_pipe.load_lora_weights(lora_repo, weight_name=weights, low_cpu_mem_usage=True,  adapter_name=lora_name)
+                            txt2img_pipe.load_lora_weights(lora_repo, weight_name=weights, adapter_name=lora_name)
                         except:
                             print("load lora error")