diff --git a/convert_flux_to_gguf.py b/convert_flux_to_gguf.py
index 28a3019..aef8eb6 100644
--- a/convert_flux_to_gguf.py
+++ b/convert_flux_to_gguf.py
@@ -8,6 +8,7 @@
 import argparse
 import contextlib
 import json
+import safetensors.torch
 import os
 import re
 import sys
@@ -177,6 +178,31 @@ def write(self) -> None:
         self.gguf_writer.write_tensors_to_file(progress=True)
         self.gguf_writer.close()
 
+# https://github.com/bghira/SimpleTuner/blob/cea2457ab063f6dedb9e697830ae68a96be90641/helpers/training/save_hooks.py#L64
+def _merge_sharded_checkpoints(folder: Path):
+    with open(folder / "diffusion_pytorch_model.safetensors.index.json", "r") as f:
+        ckpt_metadata = json.load(f) 
+    weight_map = ckpt_metadata.get("weight_map", None)
+    if weight_map is None:
+        raise KeyError("'weight_map' key not found in the shard index file.")
+
+    # Collect all unique safetensors files from weight_map
+    files_to_load = set(weight_map.values())
+    merged_state_dict = {}
+
+    # Load tensors from each unique file
+    for file_name in files_to_load:
+        part_file_path = folder /  file_name
+        if not os.path.exists(part_file_path):
+            raise FileNotFoundError(f"Part file {file_name} not found.")
+
+        with safetensors.safe_open(part_file_path, framework="pt", device="cpu") as f:
+            for tensor_key in f.keys():
+                if tensor_key in weight_map:
+                    merged_state_dict[tensor_key] = f.get_tensor(tensor_key)
+
+    return merged_state_dict
+
 
 def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(
@@ -216,10 +242,29 @@ def main() -> None:
     else:
         logging.basicConfig(level=logging.INFO)
 
-    if not args.model.is_file():
+    if not args.model.is_dir() and not args.model.is_file():
         logging.error(f"Model path {args.model} does not exist.")
         sys.exit(1)
 
+    if args.model.is_dir():
+        logging.info("Supplied a directory.")
+        merged_state_dict = None
+        files = list(args.model.glob('*.safetensors'))
+        n = len(files)
+        if n == 0:
+            logging.error("No safetensors files found.")
+            sys.exit(1)
+        if n == 1:
+            logging.info(f"Assinging {files[0]} to `args.model`")
+            args.model = files[0]
+        if n > 1:
+            assert args.model / "diffusion_pytorch_model.safetensors.index.json" in list(args.model.glob("*.*"))
+            merged_state_dict = _merge_sharded_checkpoints(args.model)
+            filepath = "merged_state_dict.safetensors"
+            safetensors.torch.save_file(merged_state_dict, filepath)
+            logging.info(f"Serialized merged state dict to {filepath}")
+            args.model = Path(filepath)
+
     if args.model.suffix != ".safetensors":
         logging.error(f"Model path {args.model} is not a safetensors file.")
         sys.exit(1)