diff --git a/scripts/run_inference.py b/scripts/run_inference.py
index 74da97c73..989aaa8ca 100644
--- a/scripts/run_inference.py
+++ b/scripts/run_inference.py
@@ -16,7 +16,7 @@
 # Third Party
 from peft import AutoPeftModelForCausalLM
 from tqdm import tqdm
-from transformers import AutoTokenizer
+from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
 
@@ -156,16 +156,22 @@ def load(
         tokenizer = AutoTokenizer.from_pretrained(checkpoint_path)
         # Apply the configs to the adapter config of this model; if no overrides
         # are provided, then the context manager doesn't have any effect.
-        with AdapterConfigPatcher(checkpoint_path, overrides):
-            try:
-                peft_model = AutoPeftModelForCausalLM.from_pretrained(checkpoint_path)
-            except OSError as e:
-                print("Failed to initialize checkpoint model!")
-                raise e
+        try:
+            with AdapterConfigPatcher(checkpoint_path, overrides):
+                try:
+                    model = AutoPeftModelForCausalLM.from_pretrained(checkpoint_path)
+                except OSError as e:
+                    print("Failed to initialize checkpoint model!")
+                    raise e
+        except FileNotFoundError:
+            print("No adapter config found! Loading as a merged model...")
+            # Unable to find the adapter config; fall back to loading as a merged model
+            model = AutoModelForCausalLM.from_pretrained(checkpoint_path)
+
         device = "cuda" if torch.cuda.is_available() else None
         print(f"Inferred device: {device}")
-        peft_model.to(device)
-        return cls(peft_model, tokenizer, device)
+        model.to(device)
+        return cls(model, tokenizer, device)
 
     def run(self, text: str, *, max_new_tokens: int) -> str:
         """Runs inference on an instance of this model.
@@ -198,7 +204,7 @@ def main():
         description="Loads a tuned model and runs an inference call(s) through it"
     )
     parser.add_argument(
-        "--model", help="Path to tuned model to be loaded", required=True
+        "--model", help="Path to tuned model / merged model to be loaded", required=True
     )
     parser.add_argument(
         "--out_file",
@@ -207,7 +213,7 @@ def main():
     )
     parser.add_argument(
         "--base_model_name_or_path",
-        help="Override for base model to be used [default: value in model adapter_config.json]",
+        help="Override for base model to be used for non-merged models [default: value in model adapter_config.json]",
         default=None,
     )
     parser.add_argument(