diff --git a/scripts/finetune.py b/scripts/finetune.py
index 47623a518..53d6d8557 100644
--- a/scripts/finetune.py
+++ b/scripts/finetune.py
@@ -255,14 +255,7 @@ def train(
 
     # Load the model and tokenizer
     LOG.info("loading model and peft_config...")
-    model, peft_config = load_model(
-        cfg.base_model,
-        cfg.base_model_config,
-        cfg.model_type,
-        tokenizer,
-        cfg,
-        adapter=cfg.adapter,
-    )
+    model, peft_config = load_model(cfg, tokenizer)
 
     if "merge_lora" in kwargs and cfg.adapter is not None:
         LOG.info("running merge of LoRA with base model")
diff --git a/src/axolotl/utils/models.py b/src/axolotl/utils/models.py
index 31e211953..9224d0f4d 100644
--- a/src/axolotl/utils/models.py
+++ b/src/axolotl/utils/models.py
@@ -78,12 +78,15 @@ def load_tokenizer(
 
 
 def load_model(
-    base_model, base_model_config, model_type, tokenizer, cfg, adapter="lora"
-):
-    # type: (str, str, str, PreTrainedTokenizerBase, DictDefault, Optional[str]) -> Tuple[PreTrainedModel, Optional[PeftConfig]]
+    cfg, tokenizer
+):  # type: (DictDefault, PreTrainedTokenizerBase) -> Tuple[PreTrainedModel, Optional[PeftConfig]]
     """
-    Load a model from a base model and a model type.
+    Load a model for a given configuration and tokenizer.
     """
+    base_model = cfg.base_model
+    base_model_config = cfg.base_model_config
+    model_type = cfg.model_type
+    adapter = cfg.adapter
 
     # TODO refactor as a kwarg
     load_in_8bit = cfg.load_in_8bit