diff --git a/convert_to_safetensors.py b/convert_to_safetensors.py
new file mode 100644
index 0000000..19d9633
--- /dev/null
+++ b/convert_to_safetensors.py
@@ -0,0 +1,45 @@
+#!/usr/bin/env python3
+"""Convert torch.save quantized shards to safetensors format."""
+
+import gc
+import torch
+from pathlib import Path
+from safetensors.torch import save_file
+import glob
+
+
+def convert_shards(model_path):
+    output_path = Path(model_path)
+    shards = sorted(glob.glob(f"{model_path}/*.safetensors"))
+    
+    print(f"Converting {len(shards)} shards to safetensors format...\n")
+    
+    for i, shard_path in enumerate(shards):
+        print(f"Converting shard {i+1}/{len(shards)}: {shard_path.name}")
+        
+        # Load torch.save format
+        ckpt = torch.load(shard_path, map_location="cpu", weights_only=False)
+        
+        # Separate tensors from QuantState objects
+        tensors = {}
+        for key, value in ckpt.items():
+            if isinstance(value, torch.Tensor):
+                tensors[key] = value
+            else:
+                # Save QuantState separately if needed
+                print(f"   Skipping non-tensor: {key} ({type(value)})")
+        
+        # Save as safetensors
+        new_path = output_path / shard_path.name
+        save_file(tensors, new_path)
+        print(f"   ✓ Saved {len(tensors)} tensors")
+        
+        # Cleanup
+        del ckpt, tensors
+        gc.collect()
+    
+    print(f"\n✅ Converted {len(shards)} shards to safetensors format")
+
+
+if __name__ == "__main__":
+    convert_shards("/data/models/Ornith-1.0-35B-nf4")