Update app.py

app.py

@@ -65,6 +65,10 @@ def get_pipe(model_id: str, lora_scale: float = 1.0):
             if "lora" in name.lower() and param.requires_grad:
                 print(f"LoRA layer: {name}, shape: {param.shape}")
                 break
+        print("LoRA layers in text_encoder:")
+        for name, param in pipe.text_encoder.named_parameters():
+            if "lora" in name:
+                print(f"Text Encoder LoRA: {name}, shape: {param.shape}")
     else:
         # Load a standard model without LoRA
         pipe = DiffusionPipeline.from_pretrained(
@@ -98,11 +102,12 @@ def infer(
         # примерная схема: словарь name->класс scheduler
         # при необходимости добавить другие scheduler'ы — импортируйте их сверху и добавьте сюда
         try:
-            from diffusers import DDIMScheduler, EulerAncestralDiscreteScheduler, PNDMScheduler
+            from diffusers import DDIMScheduler, EulerAncestralDiscreteScheduler, PNDMScheduler, DPMSolverMultistepScheduler
             sched_map = {
                 "DDIM": DDIMScheduler,
                 "EulerAncestral": EulerAncestralDiscreteScheduler,
                 "PNDM": PNDMScheduler,
+                "DPMSMS": DPMSolverMultistepScheduler
             }
             if scheduler_name in sched_map:
                 pipe.scheduler = sched_map[scheduler_name].from_config(pipe.scheduler.config)