diff --git a/eole/bin/model/average_models.py b/eole/bin/model/average_models.py
index 2d45104c..3a4b8b57 100755
--- a/eole/bin/model/average_models.py
+++ b/eole/bin/model/average_models.py
@@ -1,41 +1,37 @@
 #!/usr/bin/env python
 import torch
 from eole.bin import BaseBin, register_bin
+from eole.models import model_saver
+from eole.config import recursive_model_fields_set
+from safetensors.torch import load_file, save_file
+import os
+import json
 
 
-def average_models(model_files, fp32=False):
+def average_models(model_paths, fp32=False):
     vocab = None
     config = None
     avg_model = None
-    avg_generator = None
 
-    for i, model_file in enumerate(model_files):
-        m = torch.load(model_file, map_location="cpu")
-        model_weights = m["model"]
-        generator_weights = m["generator"]
+    for i, model_path in enumerate(model_paths):
+        m = model_saver.load_checkpoint(model_path)
+        model_weights = load_file(os.path.join(model_path, "model.00.safetensors"))
 
         if fp32:
             for k, v in model_weights.items():
                 model_weights[k] = v.float()
-            for k, v in generator_weights.items():
-                generator_weights[k] = v.float()
 
         if i == 0:
-            vocab, config = m["vocab"], m["config"]
+            vocab, config, optim = m["vocab"], m["config"], m["optim"]
             avg_model = model_weights
-            avg_generator = generator_weights
         else:
             for k, v in avg_model.items():
                 avg_model[k].mul_(i).add_(model_weights[k]).div_(i + 1)
 
-            for k, v in avg_generator.items():
-                avg_generator[k].mul_(i).add_(generator_weights[k]).div_(i + 1)
-
     final = {
         "vocab": vocab,
         "config": config,
-        "optim": None,
-        "generator": avg_generator,
+        "optim": optim,
         "model": avg_model,
     }
     return final
@@ -56,4 +52,23 @@ def add_args(cls, parser):
     @classmethod
     def run(cls, args):
         final = average_models(args.models, args.fp32)
-        torch.save(final, args.output)
+
+        if not os.path.isdir(args.output):
+            os.makedirs(args.output, exist_ok=True)
+
+        # this maybe better implemented using model_saver classes
+        # config
+        with open(os.path.join(args.output, "config.json"), "w") as f:
+            json.dump(
+                recursive_model_fields_set(final["config"]),
+                f,
+                indent=2,
+                ensure_ascii=False,
+            )
+        # vocab
+        with open(os.path.join(args.output, "vocab.json"), "w") as f:
+            json.dump(final["vocab"], f, indent=2, ensure_ascii=False)
+        # optimizer
+        torch.save(final["optim"], os.path.join(args.output, "optimizer.pt"))
+        # model weights
+        save_file(final["model"], os.path.join(args.output, "model.00.safetensors"))