Update app.py

app.py

@@ -21,22 +21,24 @@ transformer = FluxTransformer2DModel.from_pretrained(
 print("Start loading LoRA weights")
 state_dict, network_alphas = FluxFillPipeline.lora_state_dict(
     pretrained_model_name_or_path_or_dict="blanchon/FluxFillFurniture",
-    weight_name="lora_fill.safetensors",
+    weight_name="pytorch_lora_weights.safetensors",
     return_alphas=True
 )
 is_correct_format = all("lora" in key or "dora_scale" in key for key in state_dict.keys())
 if not is_correct_format:
     raise ValueError("Invalid LoRA checkpoint.")
+
+
+pipe = FluxFillPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-Fill-dev",
+    torch_dtype=torch.bfloat16
+).to(device)
 FluxFillPipeline.load_lora_into_transformer(
     state_dict=state_dict,
     network_alphas=network_alphas,
-    transformer=transformer,
+    transformer=pipe.transformer,
 )
-pipe = FluxFillPipeline.from_pretrained(
-    "black-forest-labs/FLUX.1-Fill-dev", 
-    torch_dtype=torch.bfloat16,
-    transformer=transformer,
-).to("cuda")
+
 # pipe.load_lora_weights("blanchon/FluxFillFurniture", weight_name="lora_fill.safetensors")
 # pipe.fuse_lora(lora_scale=1.0)
 pipe.to("cuda")