diff --git a/unsloth/models/llama.py b/unsloth/models/llama.py
index f310d102f4..73c78ba0bf 100644
--- a/unsloth/models/llama.py
+++ b/unsloth/models/llama.py
@@ -619,7 +619,7 @@ class FastLlamaModel:
         token = None,
         device_map = "sequential",
         rope_scaling = None,
-        check_tokenizer = True,
+        fix_tokenizer = True,
     ):
         SUPPORTS_BFLOAT16 = torch.cuda.is_bf16_supported()
         gpu_stats = torch.cuda.get_device_properties(0)
@@ -704,7 +704,7 @@ class FastLlamaModel:
         internal_model.max_seq_length = max_position_embeddings
 
         # We check the tokenizer first for errors
-        if check_tokenizer:
+        if fix_tokenizer:
             tokenizer = check_tokenizer(
                 model = model,
                 tokenizer = tokenizer,
diff --git a/unsloth/models/loader.py b/unsloth/models/loader.py
index eadf026cc9..48200c3878 100644
--- a/unsloth/models/loader.py
+++ b/unsloth/models/loader.py
@@ -44,7 +44,7 @@ class FastLanguageModel(FastLlamaModel):
         token = None,
         device_map = "sequential",
         rope_scaling = None,
-        check_tokenizer = True,
+        fix_tokenizer = True,
         *args, **kwargs,
     ):
         if not SUPPORTS_FOURBIT and model_name in FOURBIT_MAPPER:
@@ -84,7 +84,7 @@ class FastLanguageModel(FastLlamaModel):
             token = token,
             device_map = device_map,
             rope_scaling = rope_scaling,
-            check_tokenizer = check_tokenizer,
+            fix_tokenizer = fix_tokenizer,
             *args, **kwargs,
         )
     pass
diff --git a/unsloth/models/mistral.py b/unsloth/models/mistral.py
index e15a3ae9ff..e48a982b8c 100644
--- a/unsloth/models/mistral.py
+++ b/unsloth/models/mistral.py
@@ -263,7 +263,7 @@ class FastMistralModel(FastLlamaModel):
         token = None,
         device_map = "sequential",
         rope_scaling = None, # Mistral does not support RoPE scaling
-        check_tokenizer = True,
+        fix_tokenizer = True,
     ): 
         if rope_scaling is not None:
             logger.warning_once("Unsloth: Mistral models do not support RoPE scaling.")
@@ -333,7 +333,7 @@ class FastMistralModel(FastLlamaModel):
         internal_model.max_seq_length = max_position_embeddings
 
         # We check the tokenizer first for errors
-        if check_tokenizer:
+        if fix_tokenizer:
             tokenizer = check_tokenizer(
                 model = model,
                 tokenizer = tokenizer,