Update app.py

app.py

@@ -18,6 +18,8 @@ dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # Load the model pipeline
+
+# scheduler config needed for the LoRA
 # From https://github.com/ModelTC/Qwen-Image-Lightning/blob/342260e8f5468d2f24d084ce04f55e101007118b/generate_with_diffusers.py#L82C9-L97C10
 scheduler_config = {
     "base_image_seq_len": 256,
@@ -38,6 +40,14 @@ scheduler_config = {
 scheduler = FlowMatchEulerDiscreteScheduler.from_config(scheduler_config)
 pipe = QwenImageEditPipeline.from_pretrained("Qwen/Qwen-Image-Edit", scheduler=scheduler, torch_dtype=dtype).to(device)
 
+# lora loading
+pipe.load_lora_weights(
+    "lightx2v/Qwen-Image-Lightning", weight_name="Qwen-Image-Lightning-8steps-V1.0.safetensors", adapter_name="lightx2v"
+)
+pipeline.set_adapters(["lightx2v"], adapter_weights=[1.])
+pipeline.fuse_lora(adapter_names=["lightx2v"], lora_scale=1., components=["transformer"])
+pipeline.unload_lora_weights()
+
 # --- UI Constants and Helpers ---
 MAX_SEED = np.iinfo(np.int32).max