update

src/transformers/modeling_gguf_pytorch_utils.py

@@ -15,7 +15,7 @@
 # limitations under the License.
 
 import re
-from typing import Optional
+from typing import Any, Dict, Optional
 
 import numpy as np
 from tqdm import tqdm
@@ -242,7 +242,7 @@ def reverse_reshape_bias(weights: np.ndarray, n_head: int, n_embed: int):
 
 
 def split_moe_expert_tensor(
-    weights: np.ndarray, parsed_parameters: dict[str, dict], name: str, tensor_key_mapping: dict
+    weights: np.ndarray, parsed_parameters: Dict[str, Any], name: str, tensor_key_mapping: dict
 ):
     # Original merge implementation
     # https://github.com/ggerganov/llama.cpp/blob/master/convert_hf_to_gguf.py#L1994-L2022
@@ -262,4 +262,4 @@ def split_moe_expert_tensor(
     for i in range(0, w_counter):
         temp_name = name.replace(".weight", f".{i}.{exp_name}.weight")
         exp_weight = weights[i]
-        parsed_parameters["tensors"][temp_name] = torch.from_numpy(np.copy(exp_weight))
+        parsed_parameters["tensors"][temp_name] = torch.from_numpy(np.copy(exp_weight))