Don't reload model for the merge step;

Context.py

@@ -1,9 +1,12 @@
 import configparser
 import torch
 
+from peft import PeftModel
 from sympy.printing import str
 
 class Context:
+    model: PeftModel
+    
     accel: bool
     device: str
     purgeTargetDirectories: bool

Merger.py

@@ -7,15 +7,17 @@ class Merger:
     def mergeAndStore(self, context: Context):
         if not context.mergeFull:
             return
+        
+        if not context.model: 
             if not context.storeAdapter:
                 raise Exception("Configuration problem: mergeFull requires storeAdapter")
             
-        print("Reloading model")
+            print("Loading model")
             baseModel = ModelLoader().load(context.locBaseModel, False, True, context)
-        peftModel = PeftModel.from_pretrained(baseModel, context.locAdapter)
+            context.model = PeftModel.from_pretrained(baseModel, context.locAdapter)
         
         print("Merging")
-        mergedModel = peftModel.merge_and_unload()
+        mergedModel = context.model.merge_and_unload()
         
         print("Dequantize")
         try:

Trainer.py

@@ -16,7 +16,8 @@ class Trainer:
         
         baseModel = ModelLoader().load(context.locBaseModel, False, True, context)
         sftTrainer = self.__createTrainer(baseModel, context)
-        try:
+        context.model = sftTrainer.model
+        
         vInplace = context.validate and context.vInplace
         validator = None
         if vInplace:
@@ -46,13 +47,6 @@ class Trainer:
         if context.storeAdapter:
             self.__storeAdapter(sftTrainer, context)
         
-        finally:
-            del sftTrainer
-            del baseModel
-            gc.collect()
-            if context.accel:
-                torch.cuda.empty_cache()
-        
     def __createTrainer(self, baseModel, context: Context):
         tokenizer = AutoTokenizer.from_pretrained(
                 context.locBaseModel,