Update deprecated type hinting in models (#18132)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

vllm/model_executor/models/roberta.py

@@ -1,7 +1,8 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import itertools
-from typing import Iterable, Optional, Tuple, Union
+from collections.abc import Iterable
+from typing import Optional, Union
 
 import torch
 from torch import nn
@@ -135,7 +136,7 @@ class RobertaEmbeddingModel(BertEmbeddingModel):
                              prefix=prefix,
                              embedding_class=RobertaEmbedding)
 
-    def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
+    def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]):
         weights = self.hf_to_vllm_mapper.apply(weights)
         # Separate weights in "roberta"-prefixed and all else (not in memory).
         # For use with models like FacebookAI/roberta-base.
@@ -187,7 +188,7 @@ class RobertaForSequenceClassification(nn.Module, SupportsCrossEncoding,
         self.classifier = RobertaClassificationHead(config)
         self._pooler = CrossEncodingPooler(config, self.classifier)
 
-    def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
+    def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]):
         bert_weights, task_weights = roberta_task_weights_filter(weights)
         bert_weights = self.jina_to_vllm_mapper.apply(bert_weights)
 
@@ -249,8 +250,8 @@ def create_position_ids_from_input_ids(input_ids,
 
 
 def roberta_task_weights_filter(
-    all_weights: Iterable[Tuple[str, torch.Tensor]]
-) -> Tuple[Iterable[Tuple[str, torch.Tensor]], Iterable[Tuple[str,
+    all_weights: Iterable[tuple[str, torch.Tensor]]
+) -> tuple[Iterable[tuple[str, torch.Tensor]], Iterable[tuple[str,
                                                               torch.Tensor]]]:
     """
     Separate task-specific weights that are applied on top