diff --git a/src/sparsezoo/models/zoo.py b/src/sparsezoo/models/zoo.py
index 05575ca2..d7d34f37 100644
--- a/src/sparsezoo/models/zoo.py
+++ b/src/sparsezoo/models/zoo.py
@@ -541,12 +541,28 @@ def download_recipe_base_framework_files(
         stub, args = parse_zoo_stub(stub, valid_params=["recipe_type"])
         model = Zoo.load_model_from_stub(stub)
 
-        if (
-            recipe_type in args
-            and args["recipe_type"] == OptimizationRecipeTypes.TRANSFER_LEARN.value
-        ):
+        # check recipe type, default to original, and validate
+        recipe_type = args.get("recipe_type", OptimizationRecipeTypes.ORIGINAL.value)
+        valid_recipe_types = list(map(lambda typ: typ.value, OptimizationRecipeTypes))
+        if recipe_type not in valid_recipe_types:
+            raise ValueError(
+                f"Invalid recipe_type {recipe_type}. "
+                f"Valid recipe types: {valid_recipe_types}"
+            )
+
+        if recipe_type == OptimizationRecipeTypes.TRANSFER_LEARN.value:
             # return final model's optimized weights for sparse transfer learning
-            return model.download_framework_files(extensions=extensions)
+            framework_files = model.download_framework_files(extensions=extensions)
+
+            # download only pre-quantized weights if available
+            checkpoint_framework_files = [
+                framework_file
+                for framework_file in framework_files
+                if ".ckpt" in framework_file
+            ]
+
+            # return non-empty list, preferring filtered list
+            return checkpoint_framework_files or framework_files
         else:
             # search for base model, and return those weights as a starting checkpoint
             base_model = [
@@ -556,4 +572,16 @@ def download_recipe_base_framework_files(
             ]
             if not base_model:
                 raise ValueError(f"Could not find base model for model {model}")
-            return base_model[0].download_framework_files(extensions=extensions)
+            framework_files = base_model[0].download_framework_files(
+                extensions=extensions
+            )
+
+            # filter out checkpoint weights if any exist
+            base_framework_files = [
+                framework_file
+                for framework_file in framework_files
+                if ".ckpt" not in framework_file
+            ]
+
+            # return non-empty list, preferring filtered list
+            return base_framework_files or framework_files