diff --git a/backends/exllamav2/model.py b/backends/exllamav2/model.py
index 6fddc8b4..3dfa84de 100644
--- a/backends/exllamav2/model.py
+++ b/backends/exllamav2/model.py
@@ -361,6 +361,8 @@ def __init__(self, model_directory: pathlib.Path, quiet=False, **kwargs):
                 self.draft_config.max_attention_size = chunk_size**2
 
     def set_model_overrides(self, **kwargs):
+        """Sets overrides from a model folder's config yaml."""
+
         override_config_path = self.model_dir / "tabby_config.yml"
 
         if not override_config_path.exists():
diff --git a/common/model.py b/common/model.py
index d1b49afe..0f5ab55a 100644
--- a/common/model.py
+++ b/common/model.py
@@ -149,7 +149,7 @@ async def unload_embedding_model():
     embeddings_container = None
 
 
-def get_config_default(key: str, fallback=None, model_type: str = "model"):
+def get_config_default(key: str, model_type: str = "model"):
     """Fetches a default value from model config if allowed by the user."""
 
     model_config = config.model_config()
@@ -162,14 +162,12 @@ def get_config_default(key: str, fallback=None, model_type: str = "model"):
         # Is this a draft model load parameter?
         if model_type == "draft":
             draft_config = config.draft_model_config()
-            return unwrap(draft_config.get(key), fallback)
+            return draft_config.get(key)
         elif model_type == "embedding":
             embeddings_config = config.embeddings_config()
-            return unwrap(embeddings_config.get(key), fallback)
+            return embeddings_config.get(key)
         else:
-            return unwrap(model_config.get(key), fallback)
-    else:
-        return fallback
+            return model_config.get(key)
 
 
 async def check_model_container():
diff --git a/endpoints/core/types/model.py b/endpoints/core/types/model.py
index c4959fe9..dfbb0337 100644
--- a/endpoints/core/types/model.py
+++ b/endpoints/core/types/model.py
@@ -53,19 +53,19 @@ class DraftModelLoadRequest(BaseModel):
     # Config arguments
     draft_rope_scale: Optional[float] = Field(
         default_factory=lambda: get_config_default(
-            "draft_rope_scale", 1.0, model_type="draft"
+            "draft_rope_scale", model_type="draft"
         )
     )
     draft_rope_alpha: Optional[float] = Field(
         description="Automatically calculated if not present",
         default_factory=lambda: get_config_default(
-            "draft_rope_alpha", None, model_type="draft"
+            "draft_rope_alpha", model_type="draft"
         ),
         examples=[1.0],
     )
     draft_cache_mode: Optional[str] = Field(
         default_factory=lambda: get_config_default(
-            "draft_cache_mode", "FP16", model_type="draft"
+            "draft_cache_mode", model_type="draft"
         )
     )
 
@@ -97,16 +97,16 @@ class ModelLoadRequest(BaseModel):
         examples=[4096],
     )
     tensor_parallel: Optional[bool] = Field(
-        default_factory=lambda: get_config_default("tensor_parallel", False)
+        default_factory=lambda: get_config_default("tensor_parallel")
     )
     gpu_split_auto: Optional[bool] = Field(
-        default_factory=lambda: get_config_default("gpu_split_auto", True)
+        default_factory=lambda: get_config_default("gpu_split_auto")
     )
     autosplit_reserve: Optional[List[float]] = Field(
-        default_factory=lambda: get_config_default("autosplit_reserve", [96])
+        default_factory=lambda: get_config_default("autosplit_reserve")
     )
     gpu_split: Optional[List[float]] = Field(
-        default_factory=lambda: get_config_default("gpu_split", []),
+        default_factory=lambda: get_config_default("gpu_split"),
         examples=[[24.0, 20.0]],
     )
     rope_scale: Optional[float] = Field(
@@ -120,10 +120,10 @@ class ModelLoadRequest(BaseModel):
         examples=[1.0],
     )
     cache_mode: Optional[str] = Field(
-        default_factory=lambda: get_config_default("cache_mode", "FP16")
+        default_factory=lambda: get_config_default("cache_mode")
     )
     chunk_size: Optional[int] = Field(
-        default_factory=lambda: get_config_default("chunk_size", 2048)
+        default_factory=lambda: get_config_default("chunk_size")
     )
     prompt_template: Optional[str] = Field(
         default_factory=lambda: get_config_default("prompt_template")
@@ -132,7 +132,7 @@ class ModelLoadRequest(BaseModel):
         default_factory=lambda: get_config_default("num_experts_per_token")
     )
     fasttensors: Optional[bool] = Field(
-        default_factory=lambda: get_config_default("fasttensors", False)
+        default_factory=lambda: get_config_default("fasttensors")
     )
 
     # Non-config arguments
diff --git a/endpoints/core/utils/model.py b/endpoints/core/utils/model.py
index 15f85b81..cac47111 100644
--- a/endpoints/core/utils/model.py
+++ b/endpoints/core/utils/model.py
@@ -95,8 +95,10 @@ async def stream_model_load(
 ):
     """Request generation wrapper for the loading process."""
 
+    # Get trimmed load data
+    load_data = data.model_dump(exclude_none=True)
+
     # Set the draft model path if it exists
-    load_data = data.model_dump()
     if draft_model_path:
         load_data["draft"]["draft_model_dir"] = draft_model_path