Update inference_manager.py

inference_manager.py

@@ -194,7 +194,7 @@ class InferenceManager:
                 #variant="fp16",
                 custom_pipeline   = "lpw_stable_diffusion_xl",
             )
-            pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+            #pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
             clip_skip = cfg.get("clip_skip", 1)
             # Adjust clip skip for XL (assumed not relevant for SD 1.5)
             pipe.text_encoder.config.num_hidden_layers -= (clip_skip - 1)
@@ -202,7 +202,7 @@ class InferenceManager:
         load_time = round(time.time() - start, 2)
         print(f"Base model loaded in {load_time}s")
 
-        if cfg.get("load_ip_adapter_faceid", False):
+        if cfg.get("load_ip_adapter_faceid", False) and False:
             if model_version in ("pony", "xl"):
                 ip_ckpt = self.ext_model_pathes.get("ip-adapter-faceid-sdxl", "")
                 if ip_ckpt:
@@ -284,7 +284,7 @@ class InferenceManager:
         build_time = round(time.time() - start, 2)
         print(f"Pipeline built with LoRAs in {build_time}s.")
         if not sampler:
-            sampler = self.cfg.get("sampler", "DPM2 a")
+            sampler = self.cfg.get("sampler", "Euler a")
         # Define samplers
         samplers = {
             "Euler a": EulerAncestralDiscreteScheduler.from_config(temp_pipeline.scheduler.config),