[docs] Docstring typo (huggingface#1455)

* fix typo

* fix

src/peft/tuners/lora/model.py

@@ -36,7 +36,7 @@
     _get_submodules,
     get_quantization_config,
 )
-from peft.utils.merge_utils import dare_linear, dare_ties, task_arthimetic, ties
+from peft.utils.merge_utils import dare_linear, dare_ties, task_arithmetic, ties
 
 from .config import LoraConfig
 from .gptq import dispatch_gptq
@@ -558,7 +558,7 @@ def _svd_generalized_task_arithmetic_weighted_adapter(
         delta_weight = [target.get_delta_weight(adapter) for adapter in valid_adapters]
         valid_weights = torch.tensor(valid_weights).to(delta_weight[0].device)
         if combination_type == "svd":
-            delta_weight = task_arthimetic(delta_weight, valid_weights)
+            delta_weight = task_arithmetic(delta_weight, valid_weights)
         elif combination_type == "ties_svd":
             delta_weight = ties(delta_weight, valid_weights, density, majority_sign_method)
         elif combination_type == "dare_linear_svd":
@@ -625,7 +625,7 @@ def _generalized_task_arithmetic_weighted_adapter(
         dtype = lora_A_deltas[0].dtype
         for i, task_tensors in enumerate(lora_deltas):
             if combination_type == "linear":
-                lora_deltas[i] = task_arthimetic(task_tensors, valid_weights)
+                lora_deltas[i] = task_arithmetic(task_tensors, valid_weights)
             elif combination_type == "ties":
                 lora_deltas[i] = ties(task_tensors, valid_weights, density, majority_sign_method)
             elif combination_type == "dare_linear":

src/peft/utils/merge_utils.py

@@ -141,9 +141,9 @@ def disjoint_merge(task_tensors: torch.Tensor, majority_sign_mask: torch.Tensor)
     return mixed_task_tensors / torch.clamp(num_params_preserved, min=1.0)
 
 
-def task_arthimetic(task_tensors: List[torch.Tensor], weights: torch.Tensor) -> torch.Tensor:
+def task_arithmetic(task_tensors: List[torch.Tensor], weights: torch.Tensor) -> torch.Tensor:
     """
-    Merge the task tensors using `task arthimetic`.
+    Merge the task tensors using `task arithmetic`.
 
     Args:
         task_tensors(`List[torch.Tensor]`):The task tensors to merge.