diff --git a/comfy/model_base.py b/comfy/model_base.py
index 6c8ee69b4..75d469221 100644
--- a/comfy/model_base.py
+++ b/comfy/model_base.py
@@ -60,6 +60,7 @@ import math
 from typing import TYPE_CHECKING
 if TYPE_CHECKING:
     from comfy.model_patcher import ModelPatcher
+from comfy.model_management import get_free_memory
 
 class ModelType(Enum):
     EPS = 1
@@ -291,18 +292,19 @@ class BaseModel(torch.nn.Module):
         return out
 
     def load_model_weights(self, sd, unet_prefix=""):
-        import pdb; pdb.set_trace()
         to_load = {}
         keys = list(sd.keys())
         for k in keys:
             if k.startswith(unet_prefix):
                 to_load[k[len(unet_prefix):]] = sd.pop(k)
 
-        logging.info(f"load model weights start, keys {keys}")
+        free_cpu_memory = get_free_memory(torch.device("cpu"))
+        logging.info(f"load model weights start, free cpu memory size {free_cpu_memory/(1024*1024*1024)} GB")
         to_load = self.model_config.process_unet_state_dict(to_load)
-        logging.info(f"load model {self.model_config} weights process end, keys {keys}")
+        logging.info(f"load model {self.model_config} weights process end")
         m, u = self.diffusion_model.load_state_dict(to_load, strict=False)
-        logging.info(f"load model {self.model_config} weights end, keys {keys}")
+        free_cpu_memory = get_free_memory(torch.device("cpu"))
+        logging.info(f"load model {self.model_config} weights end, free cpu memory size {free_cpu_memory/(1024*1024*1024)} GB")
         if len(m) > 0:
             logging.warning("unet missing: {}".format(m))