有关bert运行的错误，如何解决？
最近在练习李宏毅的hw07，有关bert的。然后在跑第一次代码的时候，加载bert模型总是在显示权限错误，和OS加载模型错误，但是在autodl上却可以运行，我自己是在学校的服务器上面，有权限限定的，想问一下这种情况要怎么解决。
```python
[Errno 13] Permission denied: '/home/kaihua/.cache/huggingface/transformers/6cc404ca8136bc87bae0fb24f2259904943d776a6c5ddc26598bbdc319476f42.0f9bcd8314d841c06633e7b92b04509f1802c16796ee67b0f1177065739e24ae.lock'
---------------------------------------------------------------------------
PermissionError Traceback (most recent call last)
File ~/.local/lib/python3.9/site-packages/transformers/configuration_utils.py:457, in PretrainedConfig.get_config_dict(cls, pretrained_model_name_or_path, **kwargs)
455 try:
456 # Load from URL or cache if already cached
--> 457 resolved_config_file = cached_path(
458 config_file,
459 cache_dir=cache_dir,
460 force_download=force_download,
461 proxies=proxies,
462 resume_download=resume_download,
463 local_files_only=local_files_only,
464 use_auth_token=use_auth_token,
465 user_agent=user_agent,
466 )
467 # Load config dict
File ~/.local/lib/python3.9/site-packages/transformers/file_utils.py:1165, in cached_path(url_or_filename, cache_dir, force_download, proxies, resume_download, user_agent, extract_compressed_file, force_extract, use_auth_token, local_files_only)
1163 if is_remote_url(url_or_filename):
1164 # URL, so get it from the cache (downloading if necessary)
-> 1165 output_path = get_from_cache(
1166 url_or_filename,
1167 cache_dir=cache_dir,
1168 force_download=force_download,
1169 proxies=proxies,
1170 resume_download=resume_download,
1171 user_agent=user_agent,
1172 use_auth_token=use_auth_token,
1173 local_files_only=local_files_only,
1174 )
1175 elif os.path.exists(url_or_filename):
1176 # File, and it exists.
File ~/.local/lib/python3.9/site-packages/transformers/file_utils.py:1399, in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, use_auth_token, local_files_only)
1398 lock_path = cache_path + ".lock"
-> 1399 with FileLock(lock_path):
1400
1401 # If the download just completed while the lock was activated.
1402 if os.path.exists(cache_path) and not force_download:
1403 # Even if returning early like here, the lock will be released.
File ~/.local/lib/python3.9/site-packages/filelock/_api.py:220, in BaseFileLock.__enter__(self)
215 """
216 Acquire the lock.
217
218 :return: the lock object
219 """
--> 220 self.acquire()
221 return self
File ~/.local/lib/python3.9/site-packages/filelock/_api.py:173, in BaseFileLock.acquire(self, timeout, poll_interval, poll_intervall, blocking)
172 _LOGGER.debug("Attempting to acquire lock %s on %s", lock_id, lock_filename)
--> 173 self._acquire()
175 if self.is_locked:
File ~/.local/lib/python3.9/site-packages/filelock/_unix.py:35, in UnixFileLock._acquire(self)
34 open_mode = os.O_RDWR | os.O_CREAT | os.O_TRUNC
---> 35 fd = os.open(self._lock_file, open_mode)
36 try:
PermissionError: [Errno 13] Permission denied: '/home/kaihua/.cache/huggingface/transformers/6cc404ca8136bc87bae0fb24f2259904943d776a6c5ddc26598bbdc319476f42.0f9bcd8314d841c06633e7b92b04509f1802c16796ee67b0f1177065739e24ae.lock'
During handling of the above exception, another exception occurred:
OSError Traceback (most recent call last)
Input In [5], in | 1>()
----> 1 model = BertForQuestionAnswering.from_pretrained("bert-base-chinese").to(device)
2 tokenizer = BertTokenizerFast.from_pretrained("bert-base-chinese")
File ~/.local/lib/python3.9/site-packages/transformers/modeling_utils.py:975, in PreTrainedModel.from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
973 if not isinstance(config, PretrainedConfig):
974 config_path = config if config is not None else pretrained_model_name_or_path
--> 975 config, model_kwargs = cls.config_class.from_pretrained(
976 config_path,
977 *model_args,
978 cache_dir=cache_dir,
979 return_unused_kwargs=True,
980 force_download=force_download,
981 resume_download=resume_download,
982 proxies=proxies,
983 local_files_only=local_files_only,
984 use_auth_token=use_auth_token,
985 revision=revision,
986 _from_auto=from_auto_class,
987 _from_pipeline=from_pipeline,
988 **kwargs,
989 )
990 else:
991 model_kwargs = kwargs
File ~/.local/lib/python3.9/site-packages/transformers/configuration_utils.py:401, in PretrainedConfig.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
331 @classmethod
332 def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs) -> "PretrainedConfig":
333 r"""
334 Instantiate a :class:`~transformers.PretrainedConfig` (or a derived class) from a pretrained model
335 configuration.
(...)
399
400 """
--> 401 config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs)
402 if config_dict.get("model_type", False) and hasattr(cls, "model_type"):
403 assert (
404 config_dict["model_type"] == cls.model_type
405 ), f"You tried to initiate a model of type '{cls.model_type}' with a pretrained model of type '{config_dict['model_type']}'"
File ~/.local/lib/python3.9/site-packages/transformers/configuration_utils.py:477, in PretrainedConfig.get_config_dict(cls, pretrained_model_name_or_path, **kwargs)
471 logger.error(err)
472 msg = (
473 f"Can't load config for '{pretrained_model_name_or_path}'. Make sure that:\n\n"
474 f"- '{pretrained_model_name_or_path}' is a correct model identifier listed on 'https://huggingface.co/models'\n\n"
475 f"- or '{pretrained_model_name_or_path}' is the correct path to a directory containing a {CONFIG_NAME} file\n\n"
476 )
--> 477 raise EnvironmentError(msg)
479 except json.JSONDecodeError:
480 msg = (
481 f"Couldn't reach server at '{config_file}' to download configuration file or "
482 "configuration file is not a valid JSON file. "
483 f"Please check network or file content here: {resolved_config_file}."
484 )
OSError: Can't load config for 'bert-base-chinese'. Make sure that:
- 'bert-base-chinese' is a correct model identifier listed on 'https://huggingface.co/models'
- or 'bert-base-chinese' is the correct path to a directory containing a config.json file
| ```
望采纳！！！点击回答右侧采纳即可！！
这种情况可能是因为你在学校的服务器上没有足够的权限来加载BERT模型。这种情况可以通过以下几种方法来解决：
请求管理员提供权限：可以向你所在学校的IT部门或服务器管理员请求权限。
在本地使用模型：可以将BERT模型下载到本地进行训练和测试，然后再将结果上传到服务器上。
使用云服务：可以使用云服务商提供的计算资源来运行BERT模型。这样可以避免权限问题，并且可以更方便地管理资源。
使用Docker: 试试在Docker容器中加载模型
不同的解决方案对于不同的场景和需求是有所不同的，希望这些建议能够帮助你解决问题。
- 给你找了一篇非常好的博客，你可以看看是否有帮助，链接：对Bert的理解
这个错误是由于在本地机器上没有足够的权限来创建和写入文件（/home/kaihua/.cache/huggingface/transformers/...）导致的。可以试试以下几种解决方法：
1、使用sudo来运行代码，以获得更高的权限。
2、将文件夹/home/kaihua/.cache/huggingface/transformers/的权限更改为自己的用户帐户有写入权限： chmod -R 755 /home/kaihua/.cache/huggingface/transformers/
3、在代码中设置cache_dir参数，将缓存目录更改为有写入权限的目录。
可以根据现在所在机器的实际权限来决定使用哪种方法。
仅供参考，望采纳，谢谢。
感觉这就是系统给到的权限不够啊，无法写入导致。