Update app.py

app.py

@@ -19,7 +19,7 @@ pipe_no_lora = ZImagePipeline.from_pretrained(
 )
 pipe.load_lora_weights("Shakker-Labs/AWPortrait-Z", weight_name="AWPortrait-Z.safetensors", adapter_name="lora")
 pipe.set_adapters(["lora",], adapter_weights=[1.])
-pipe.fuse_lora(adapter_names=["lora"], lora_scale=1)
+pipe.fuse_lora(adapter_names=["lora"], lora_scale=.9)
 pipe.unload_lora_weights()
 pipe.to("cuda")
 pipe_no_lora.to("cuda")
@@ -74,7 +74,8 @@ with gr.Blocks() as demo:
         """
         # Z-Image-Turbo Portrait✨
         
-        Generate high-quality portrait images with [Tongyi-MAI/Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo) using [portrait-beauty LoRA by Shakker Labs](https://huggingface.co/Shakker-Labs/AWPortrait-Z), for fast inference with enhanced details. 
+        Generate high-quality portrait images with [Tongyi-MAI/Z-Image-Turbo](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo) using [portrait-beauty LoRA by @dynamicwangs
+  and Shakker Labs](https://huggingface.co/Shakker-Labs/AWPortrait-Z), for fast inference with enhanced details. 
         This turbo model generates images in just 8 inference steps!
         """
     )