Update save.py

unsloth/save.py

@@ -552,6 +552,8 @@ def unsloth_save_model(
 
     max_vram = int(torch.cuda.get_device_properties(0).total_memory * maximum_memory_usage)
 
+    print("Unsloth: Saving model... This might take 5 minutes ...")
+
     from tqdm import tqdm as ProgressBar
     for j, layer in enumerate(ProgressBar(internal_model.model.layers)):
         for item in LLAMA_WEIGHTS:
@@ -668,8 +670,6 @@ def unsloth_save_model(
         print()
     pass
 
-    print("Unsloth: Saving model... This might take 5 minutes for Llama-7b...")
-
     # Since merged, edit quantization_config
     old_config = model.config
     new_config = model.config.to_dict()
@@ -1028,6 +1028,7 @@ def save_to_gguf(
     quantize_location = get_executable(["llama-quantize", "quantize"])
     convert_location  = get_executable(["convert-hf-to-gguf.py", "convert_hf_to_gguf.py"])
     
+    error = 0
     if quantize_location is not None and convert_location is not None:
         print("Unsloth: llama.cpp found in the system. We shall skip installation.")
     else:
@@ -1036,6 +1037,12 @@ def save_to_gguf(
             _run_installer, IS_CMAKE = _run_installer
 
             error = _run_installer.wait()
+            # Check if successful
+            if error != 0:
+                print(f"Unsloth: llama.cpp error code = {error}.")
+                install_llama_cpp_old(-10)
+            pass
+
             if IS_CMAKE:
                 # CMAKE needs to do some extra steps
                 print("Unsloth: CMAKE detected. Finalizing some steps for installation.")
@@ -1050,12 +1057,6 @@ def save_to_gguf(
             install_llama_cpp_blocking()
         pass
 
-        # Check if successful
-        if error != 0 or quantize_location is None or convert_location is None:
-            print(f"Unsloth: llama.cpp error code = {error}.")
-            install_llama_cpp_old(-10)
-        pass
-
         # Careful llama.cpp/quantize changed to llama.cpp/llama-quantize
         # and llama.cpp/main changed to llama.cpp/llama-cli
         # See https://github.com/ggerganov/llama.cpp/pull/7809