diff --git a/extensions_built_in/sd_trainer/SDTrainer.py b/extensions_built_in/sd_trainer/SDTrainer.py
index ffe8aff6..066969a1 100644
--- a/extensions_built_in/sd_trainer/SDTrainer.py
+++ b/extensions_built_in/sd_trainer/SDTrainer.py
@@ -227,37 +227,30 @@ class SDTrainer(BaseSDTrainProcess):
 
         if self.train_config.correct_pred_norm and not is_reg:
             with torch.no_grad():
+                # this only works if doing a prior pred
+                if prior_pred is not None:
+                    prior_mean = prior_pred.mean([2,3], keepdim=True)
+                    prior_std = prior_pred.std([2,3], keepdim=True)
+                    noise_mean = noise_pred.mean([2,3], keepdim=True)
+                    noise_std = noise_pred.std([2,3], keepdim=True)
 
-                # adjust the noise target in the opposite direction of the noise pred mean and std offset
-                # this will  apply additional force the model to correct itself to match the norm of the noise
-                noise_pred_mean, noise_pred_std = get_mean_std(noise_pred)
-                noise_mean, noise_std = get_mean_std(noise)
+                    mean_adjust = prior_mean - noise_mean
+                    std_adjust = prior_std - noise_std
 
-                # apply the inverse offset of the mean and std to the noise
-                noise_additional_mean = noise_mean - noise_pred_mean
-                noise_additional_std = noise_std - noise_pred_std
+                    mean_adjust = mean_adjust * self.train_config.correct_pred_norm_multiplier
+                    std_adjust = std_adjust * self.train_config.correct_pred_norm_multiplier
 
-                # adjust for multiplier
-                noise_additional_mean = noise_additional_mean * self.train_config.correct_pred_norm_multiplier
-                noise_additional_std = noise_additional_std * self.train_config.correct_pred_norm_multiplier
+                    target_mean = noise_mean + mean_adjust
+                    target_std = noise_std + std_adjust
 
-                noise_target_std = noise_std + noise_additional_std
-                noise_target_mean = noise_mean + noise_additional_mean
+                    eps = 1e-5
 
-
-                noise_pred_target_std = noise_pred_std - noise_additional_std
-                noise_pred_target_mean = noise_pred_mean - noise_additional_mean
-                noise_pred_target_std = noise_pred_target_std.detach()
-                noise_pred_target_mean = noise_pred_target_mean.detach()
-
-                # match the noise to the target
-                noise = (noise - noise_mean) / noise_std
-                noise = noise * noise_target_std + noise_target_mean
-                noise = noise.detach()
-
-            # meatch the noise pred to the target
-            # noise_pred = (noise_pred - noise_pred_mean) / noise_pred_std
-            # noise_pred = noise_pred * noise_pred_target_std + noise_pred_target_mean
+                    # adjust the noise target to match the current knowledge of the model
+                    # noise_mean, noise_std = get_mean_std(noise)
+                    # match the noise to the prior
+                    noise = (noise - noise_mean) / (noise_std + eps)
+                    noise = noise * (target_std + eps) + target_mean
+                    noise = noise.detach()
 
         if self.train_config.inverted_mask_prior and prior_pred is not None and has_mask:
             assert not self.train_config.train_turbo
diff --git a/toolkit/config_modules.py b/toolkit/config_modules.py
index b8b788df..19861c4d 100644
--- a/toolkit/config_modules.py
+++ b/toolkit/config_modules.py
@@ -306,6 +306,7 @@ class ModelConfig:
         self.refiner_name_or_path = kwargs.get('refiner_name_or_path', None)
         self._original_refiner_name_or_path = self.refiner_name_or_path
         self.refiner_start_at = kwargs.get('refiner_start_at', 0.5)
+        self.lora_path = kwargs.get('lora_path', None)
 
         # only for SDXL models for now
         self.use_text_encoder_1: bool = kwargs.get('use_text_encoder_1', True)
diff --git a/toolkit/stable_diffusion_model.py b/toolkit/stable_diffusion_model.py
index f485366c..e10239ca 100644
--- a/toolkit/stable_diffusion_model.py
+++ b/toolkit/stable_diffusion_model.py
@@ -281,6 +281,12 @@ class StableDiffusion:
         self.unet.requires_grad_(False)
         self.unet.eval()
 
+        # load any loras we have
+        if self.model_config.lora_path is not None:
+            pipe.load_lora_weights(self.model_config.lora_path, adapter_name="lora1")
+            pipe.fuse_lora()
+            self.unet.fuse_lora()
+
         self.tokenizer = tokenizer
         self.text_encoder = text_encoder
         self.pipeline = pipe