Update app.py

app.py

@@ -333,9 +333,11 @@ scheduler_config = {
 scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
 
 # Load the model pipeline
-pipe = QwenImagePipeline.from_pretrained("Qwen/Qwen-Image-2512", scheduler=scheduler, torch_dtype=dtype).to(device)
+pipe = QwenImagePipeline.from_pretrained("Qwen/Qwen-Image-2512", 
+                                         # scheduler=scheduler, 
+                                         torch_dtype=dtype).to(device)
 pipe.load_lora_weights(
-    "lightx2v/Qwen-Image-Lightning", weight_name="Qwen-Image-Lightning-8steps-V2.0-bf16.safetensors"
+    "lightx2v/Qwen-Image-2512-Lightning", weight_name="Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
 )
 pipe.fuse_lora()
 pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
@@ -374,7 +376,7 @@ def infer(
     randomize_seed=False,
     aspect_ratio="16:9",
     guidance_scale=1.0,
-    num_inference_steps=8,
+    num_inference_steps=4,
     prompt_enhance=False,
     progress=gr.Progress(track_tqdm=True),
 ):
@@ -440,7 +442,7 @@ with gr.Blocks(css=css) as demo:
         gr.HTML("""
         <div id="logo-title">
             <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/qwen_image_logo.png" alt="Qwen-Image Logo" width="400" style="display: block; margin: 0 auto;">
-            <h2 style="font-style: italic;color: #5b47d1;margin-top: -33px !important;text-align: center;">Fast, 8-steps with Lightining LoRA</h2>
+            <h2 style="font-style: italic;color: #5b47d1;margin-top: -33px !important;text-align: center;">Fast, 4-steps with Lightx2v Lightining LoRA</h2>
         </div>
         """)
         gr.Markdown("[Learn more](https://github.com/QwenLM/Qwen-Image) about the Qwen-Image series. Try on [Qwen Chat](https://chat.qwen.ai/), or [download model](https://huggingface.co/Qwen/Qwen-Image) to run locally with ComfyUI or diffusers.")
@@ -490,7 +492,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=20,
                     step=1,
-                    value=8,
+                    value=4,
                 )
 
         gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=False)