We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Typo in deberta_v2/__init__.py
https://github.com/huggingface/transformers/blob/c503a1c15ec1b11e69a3eaaf06edfa87c05a2849/src/transformers/models/deberta_v2/__init__.py#L31
Should be '' DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST ''.

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `src/transformers/models/deberta_v2/__init__.py`
Content:
```
1 # flake8: noqa
2 # There's no way to ignore "F401 '...' imported but unused" warnings in this
3 # module, but to preserve other warnings. So, don't check this module at all.
4 
5 # Copyright 2020 The HuggingFace Team. All rights reserved.
6 #
7 # Licensed under the Apache License, Version 2.0 (the "License");
8 # you may not use this file except in compliance with the License.
9 # You may obtain a copy of the License at
10 #
11 #     http://www.apache.org/licenses/LICENSE-2.0
12 #
13 # Unless required by applicable law or agreed to in writing, software
14 # distributed under the License is distributed on an "AS IS" BASIS,
15 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
16 # See the License for the specific language governing permissions and
17 # limitations under the License.
18 
19 from typing import TYPE_CHECKING
20 
21 from ...file_utils import _BaseLazyModule, is_torch_available
22 
23 
24 _import_structure = {
25     "configuration_deberta_v2": ["DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaV2Config"],
26     "tokenization_deberta_v2": ["DebertaV2Tokenizer"],
27 }
28 
29 if is_torch_available():
30     _import_structure["modeling_deberta_v2"] = [
31         "DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
32         "DebertaV2ForSequenceClassification",
33         "DebertaV2Model",
34         "DebertaV2ForMaskedLM",
35         "DebertaV2PreTrainedModel",
36         "DebertaV2ForTokenClassification",
37         "DebertaV2ForQuestionAnswering",
38     ]
39 
40 
41 if TYPE_CHECKING:
42     from .configuration_deberta_v2 import DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaV2Config
43     from .tokenization_deberta_v2 import DebertaV2Tokenizer
44 
45     if is_torch_available():
46         from .modeling_deberta_v2 import (
47             DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
48             DebertaV2ForMaskedLM,
49             DebertaV2ForQuestionAnswering,
50             DebertaV2ForSequenceClassification,
51             DebertaV2ForTokenClassification,
52             DebertaV2Model,
53             DebertaV2PreTrainedModel,
54         )
55 
56 else:
57     import importlib
58     import os
59     import sys
60 
61     class _LazyModule(_BaseLazyModule):
62         """
63         Module class that surfaces all objects but only performs associated imports when the objects are requested.
64         """
65 
66         __file__ = globals()["__file__"]
67         __path__ = [os.path.dirname(__file__)]
68 
69         def _get_module(self, module_name: str):
70             return importlib.import_module("." + module_name, self.__name__)
71 
72     sys.modules[__name__] = _LazyModule(__name__, _import_structure)
73
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/src/transformers/models/deberta_v2/__init__.py b/src/transformers/models/deberta_v2/__init__.py
--- a/src/transformers/models/deberta_v2/__init__.py
+++ b/src/transformers/models/deberta_v2/__init__.py
@@ -28,7 +28,7 @@
 
 if is_torch_available():
     _import_structure["modeling_deberta_v2"] = [
-        "DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
+        "DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
         "DebertaV2ForSequenceClassification",
         "DebertaV2Model",
         "DebertaV2ForMaskedLM",

{"golden_diff": "diff --git a/src/transformers/models/deberta_v2/__init__.py b/src/transformers/models/deberta_v2/__init__.py\n--- a/src/transformers/models/deberta_v2/__init__.py\n+++ b/src/transformers/models/deberta_v2/__init__.py\n@@ -28,7 +28,7 @@\n \n if is_torch_available():\n     _import_structure[\"modeling_deberta_v2\"] = [\n-        \"DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST\",\n+        \"DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST\",\n         \"DebertaV2ForSequenceClassification\",\n         \"DebertaV2Model\",\n         \"DebertaV2ForMaskedLM\",\n", "issue": "Typo in deberta_v2/__init__.py\nhttps://github.com/huggingface/transformers/blob/c503a1c15ec1b11e69a3eaaf06edfa87c05a2849/src/transformers/models/deberta_v2/__init__.py#L31\r\nShould be '' DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST ''.\n", "before_files": [{"content": "# flake8: noqa\n# There's no way to ignore \"F401 '...' imported but unused\" warnings in this\n# module, but to preserve other warnings. So, don't check this module at all.\n\n# Copyright 2020 The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import TYPE_CHECKING\n\nfrom ...file_utils import _BaseLazyModule, is_torch_available\n\n\n_import_structure = {\n    \"configuration_deberta_v2\": [\"DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP\", \"DebertaV2Config\"],\n    \"tokenization_deberta_v2\": [\"DebertaV2Tokenizer\"],\n}\n\nif is_torch_available():\n    _import_structure[\"modeling_deberta_v2\"] = [\n        \"DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST\",\n        \"DebertaV2ForSequenceClassification\",\n        \"DebertaV2Model\",\n        \"DebertaV2ForMaskedLM\",\n        \"DebertaV2PreTrainedModel\",\n        \"DebertaV2ForTokenClassification\",\n        \"DebertaV2ForQuestionAnswering\",\n    ]\n\n\nif TYPE_CHECKING:\n    from .configuration_deberta_v2 import DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaV2Config\n    from .tokenization_deberta_v2 import DebertaV2Tokenizer\n\n    if is_torch_available():\n        from .modeling_deberta_v2 import (\n            DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,\n            DebertaV2ForMaskedLM,\n            DebertaV2ForQuestionAnswering,\n            DebertaV2ForSequenceClassification,\n            DebertaV2ForTokenClassification,\n            DebertaV2Model,\n            DebertaV2PreTrainedModel,\n        )\n\nelse:\n    import importlib\n    import os\n    import sys\n\n    class _LazyModule(_BaseLazyModule):\n        \"\"\"\n        Module class that surfaces all objects but only performs associated imports when the objects are requested.\n        \"\"\"\n\n        __file__ = globals()[\"__file__\"]\n        __path__ = [os.path.dirname(__file__)]\n\n        def _get_module(self, module_name: str):\n            return importlib.import_module(\".\" + module_name, self.__name__)\n\n    sys.modules[__name__] = _LazyModule(__name__, _import_structure)\n", "path": "src/transformers/models/deberta_v2/__init__.py"}], "after_files": [{"content": "# flake8: noqa\n# There's no way to ignore \"F401 '...' imported but unused\" warnings in this\n# module, but to preserve other warnings. So, don't check this module at all.\n\n# Copyright 2020 The HuggingFace Team. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom typing import TYPE_CHECKING\n\nfrom ...file_utils import _BaseLazyModule, is_torch_available\n\n\n_import_structure = {\n    \"configuration_deberta_v2\": [\"DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP\", \"DebertaV2Config\"],\n    \"tokenization_deberta_v2\": [\"DebertaV2Tokenizer\"],\n}\n\nif is_torch_available():\n    _import_structure[\"modeling_deberta_v2\"] = [\n        \"DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST\",\n        \"DebertaV2ForSequenceClassification\",\n        \"DebertaV2Model\",\n        \"DebertaV2ForMaskedLM\",\n        \"DebertaV2PreTrainedModel\",\n        \"DebertaV2ForTokenClassification\",\n        \"DebertaV2ForQuestionAnswering\",\n    ]\n\n\nif TYPE_CHECKING:\n    from .configuration_deberta_v2 import DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaV2Config\n    from .tokenization_deberta_v2 import DebertaV2Tokenizer\n\n    if is_torch_available():\n        from .modeling_deberta_v2 import (\n            DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,\n            DebertaV2ForMaskedLM,\n            DebertaV2ForQuestionAnswering,\n            DebertaV2ForSequenceClassification,\n            DebertaV2ForTokenClassification,\n            DebertaV2Model,\n            DebertaV2PreTrainedModel,\n        )\n\nelse:\n    import importlib\n    import os\n    import sys\n\n    class _LazyModule(_BaseLazyModule):\n        \"\"\"\n        Module class that surfaces all objects but only performs associated imports when the objects are requested.\n        \"\"\"\n\n        __file__ = globals()[\"__file__\"]\n        __path__ = [os.path.dirname(__file__)]\n\n        def _get_module(self, module_name: str):\n            return importlib.import_module(\".\" + module_name, self.__name__)\n\n    sys.modules[__name__] = _LazyModule(__name__, _import_structure)\n", "path": "src/transformers/models/deberta_v2/__init__.py"}]}