diff --git a/inference/convert.py b/inference/convert.py
index 3277cea..1e68e9f 100644
--- a/inference/convert.py
+++ b/inference/convert.py
@@ -42,19 +42,19 @@ MAPPING: TensorMapping = {
 def validate_paths(hf_ckpt_path: str, save_path: str) -> None:
     """Validate input and output paths."""
     if not os.path.isdir(hf_ckpt_path):
+        logger.error(f"Input directory {hf_ckpt_path} does not exist")
         raise ValueError(f"Input directory {hf_ckpt_path} does not exist")
     
     os.makedirs(save_path, exist_ok=True)
     if not os.access(save_path, os.W_OK):
+        logger.error(f"No write permission for output directory {save_path}")
         raise PermissionError(f"No write permission for output directory {save_path}")
 
 def process_tensor_name(name: str) -> str:
     """Process and normalize tensor names."""
-    # Remove 'model.' prefix if present
     if name.startswith("model."):
         name = name[len("model."):]
     
-    # Replace specific patterns
     replacements = {
         "self_attn": "attn",
         "mlp": "ffn",
@@ -73,8 +73,8 @@ def split_tensor(param: torch.Tensor, dim: Optional[int], mp: int, idx: int) ->
         return param
     
     if param.size(dim) % mp != 0:
-        raise ValueError(f"Dimension {dim} of tensor with shape {param.shape} "
-                         f"is not divisible by model parallelism factor {mp}")
+        logger.error(f"Dimension {dim} of tensor with shape {param.shape} is not divisible by model parallelism factor {mp}")
+        raise ValueError(f"Dimension {dim} of tensor with shape {param.shape} is not divisible by model parallelism factor {mp}")
     
     shard_size = param.size(dim) // mp
     return param.narrow(dim, idx * shard_size, shard_size).contiguous()
@@ -86,8 +86,7 @@ def process_checkpoint_files(
     state_dicts: List[Dict[str, torch.Tensor]]
 ) -> None:
     """Process all checkpoint files and populate state dictionaries."""
-    for file_path in tqdm(glob(os.path.join(hf_ckpt_path, "*.safetensors")), 
-                        desc="Processing checkpoint files"):
+    for file_path in tqdm(glob(os.path.join(hf_ckpt_path, "*.safetensors")), desc="Processing checkpoint files"):
         try:
             with safe_open(file_path, framework="pt", device="cpu") as f:
                 for name in tqdm(f.keys(), desc=f"Processing {os.path.basename(file_path)}", leave=False):
@@ -100,6 +99,7 @@ def process_checkpoint_files(
                     
                     key = processed_name.split(".")[-2]
                     if key not in MAPPING:
+                        logger.error(f"Unexpected tensor key: {key} in tensor {name}")
                         raise KeyError(f"Unexpected tensor key: {key} in tensor {name}")
                     
                     new_key, dim = MAPPING[key]
@@ -128,7 +128,10 @@ def save_output_files(
         output_file = os.path.join(save_path, f"model{i}-mp{mp}.safetensors")
         save_file(state_dicts[i], output_file, metadata={"format": "pt"})
     
-    # Copy token-related files
+    copy_token_files(hf_ckpt_path, save_path)
+
+def copy_token_files(hf_ckpt_path: str, save_path: str) -> None:
+    """Copy token-related files from the checkpoint path to the save path."""
     for file_path in glob(os.path.join(hf_ckpt_path, "*token*")):
         try:
             shutil.copy(file_path, os.path.join(save_path, os.path.basename(file_path)))