diff --git a/nodes/model_optimization_nodes.py b/nodes/model_optimization_nodes.py
index 418ddb4..5626934 100644
--- a/nodes/model_optimization_nodes.py
+++ b/nodes/model_optimization_nodes.py
@@ -218,21 +218,22 @@ class DiffusionModelLoaderKJ(BaseLoaderKJ):
         return (model,)
 
 def patched_patch_model(self, device_to=None, lowvram_model_memory=0, load_weights=True, force_patch_weights=False):
-    
-    if lowvram_model_memory == 0:
-        full_load = True
-    else:
-        full_load = False
-    
-    device_to = mm.get_torch_device()
-    load_weights = True
-    if load_weights:
+    with self.use_ejected():
+
+        if lowvram_model_memory == 0:
+            full_load = True
+        else:
+            full_load = False
+
+        device_to = mm.get_torch_device()
         self.load(device_to, lowvram_model_memory=lowvram_model_memory, force_patch_weights=force_patch_weights, full_load=full_load)
-    for k in self.object_patches:
-        old = comfy.utils.set_attr(self.model, k, self.object_patches[k])
-        if k not in self.object_patches_backup:
-            self.object_patches_backup[k] = old
-    
+
+        for k in self.object_patches:
+            old = comfy.utils.set_attr(self.model, k, self.object_patches[k])
+            if k not in self.object_patches_backup:
+                self.object_patches_backup[k] = old
+       
+    self.inject_model()
     return self.model
 
 def patched_load_lora_for_models(model, clip, lora, strength_model, strength_clip):
@@ -248,6 +249,7 @@ def patched_load_lora_for_models(model, clip, lora, strength_model, strength_cli
     if clip is not None:
         key_map = comfy.lora.model_lora_keys_clip(clip.cond_stage_model, key_map)
 
+    lora = comfy.lora_convert.convert_lora(lora)
     loaded = comfy.lora.load_lora(lora, key_map)
     #print(temp_object_patches_backup)