Update app.py

app.py

@@ -14,6 +14,8 @@ MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048
 
 pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16).to("cuda")
+pipe.load_lora_weights("alvdansen/flux-koda")
+pipe.enable_sequential_cpu_offload()
 
 def calculate_optimal_dimensions(image: Image.Image):
     # Extract the original dimensions
@@ -67,7 +69,8 @@ def infer(edit_images, prompt, seed=42, randomize_seed=False, width=1024, height
         width=width,
         guidance_scale=guidance_scale,
         num_inference_steps=num_inference_steps,
-        generator=torch.Generator("cpu").manual_seed(seed)
+        generator=torch.Generator("cpu").manual_seed(seed),
+        lora_scale=0.75
     ).images[0]
 
     output_image_jpg = image.convert("RGB")