diff --git a/src/axolotl/core/trainers/grpo/__init__.py b/src/axolotl/core/trainers/grpo/__init__.py
index 3e824f705..2c6eb8c6f 100644
--- a/src/axolotl/core/trainers/grpo/__init__.py
+++ b/src/axolotl/core/trainers/grpo/__init__.py
@@ -2,8 +2,11 @@
 
 import importlib
 import inspect
+import os
 from typing import Any
 
+from huggingface_hub import snapshot_download
+from requests import HTTPError
 from trl.trainer.grpo_trainer import RewardFunc
 
 from axolotl.core.trainers.grpo.args import AxolotlGRPOConfig
@@ -178,9 +181,18 @@ class GRPOStrategy:
                     "Reward function must accept at least two arguments: prompts: list and completions: list"
                 )
             return reward_func
-        except ModuleNotFoundError:
+        except ModuleNotFoundError as exc:
             # the user has passed a string (ideally indicating the path of a reward model)
-            LOG.info(
-                f"Reward function {reward_func_fqn} is a pre-trained model path - if this is unexpected, please check the reward function path."
-            )
-            return reward_func_fqn
+            # check if it's a local dir path and not empty dir to a reward model
+            pretrained_log_msg = f"Reward function {reward_func_fqn} is a pre-trained model path - if this is unexpected, please check the reward function path."
+            if os.path.isdir(reward_func_fqn) and os.listdir(reward_func_fqn):
+                LOG.info(pretrained_log_msg)
+                return reward_func_fqn
+            try:
+                snapshot_download(reward_func_fqn, repo_type="model")
+                LOG.info(pretrained_log_msg)
+                return reward_func_fqn
+            except HTTPError:
+                raise ValueError(
+                    f"Reward function {reward_func_fqn} not found."
+                ) from exc