在使用DPOTrainer的训练后，我将其保存在本地，如下所示，然后使用AutoPeftModelForCauseLM加载它，然后出现错误。当我以同样的方式加载SFTTranier本地存储的检查点时，我没有得到错误。我把token（没有问题）和其他东西。但我一直得到同样的错误。我请求帮助。谢谢。

dpo_trainer.model.save_pretrained(path_save_dpo)
tokenizer.save_pretrained(path_save_dpo)

字符串
第一个月

os.listdir("./model/dpo_results/final_checkpoint")

['README.md', 'adapter_model.bin', 'adapter_config.json', 'tokenizer_config.json', 'special_tokens_map.json', 'vocab.json', 'merges.txt', 'tokenizer.json']

import torch
from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer, AutoModelForCausalLM

DEV = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
adapter_path = "./model/dpo_results/final_checkpoint"
model = AutoPeftModelForCausalLM.from_pretrained(
adapter_path,
torch_dtype=torch.bfloat16,
load_in_4bit=True,
token = HUGGINGFACEHUB_API_TOKEN,
)
tokenizer = AutoTokenizer.from_pretrained(adapter_path)

HTTPError                                 Traceback (most recent call last)
File c:\Users\nl202\miniconda3\envs\py31006th\lib\site-packages\huggingface_hub\utils\_errors.py:261, in hf_raise_for_status(response, endpoint_name)
    260 try:
--> 261     response.raise_for_status()
    262 except HTTPError as e:

File c:\Users\nl202\miniconda3\envs\py31006th\lib\site-packages\requests\models.py:1021, in Response.raise_for_status(self)
   1020 if http_error_msg:
-> 1021     raise HTTPError(http_error_msg, response=self)

HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/None/resolve/main/config.json

The above exception was the direct cause of the following exception:

RepositoryNotFoundError                   Traceback (most recent call last)
File c:\Users\nl202\miniconda3\envs\py31006th\lib\site-packages\transformers\utils\hub.py:428, in cached_file(path_or_repo_id, filename, cache_dir, force_download, resume_download, proxies, token, revision, local_files_only, subfolder, repo_type, user_agent, _raise_exceptions_for_missing_entries, _raise_exceptions_for_connection_errors, _commit_hash, **deprecated_kwargs)
    426 try:
    427     # Load from URL or cache if already cached
--> 428     resolved_file = hf_hub_download(
    429         path_or_repo_id,
    430         filename,
    431         subfolder=None if len(subfolder) == 0 else subfolder,
    432         repo_type=repo_type,
    433         revision=revision,
    434         cache_dir=cache_dir,
    435         user_agent=user_agent,
    436         force_download=force_download,
    437         proxies=proxies,
    438         resume_download=resume_download,
    439         token=token,
    440         local_files_only=local_files_only,
    441     )
    442 except GatedRepoError as e:

File c:\Users\nl202\miniconda3\envs\py31006th\lib\site-packages\huggingface_hub\utils\_validators.py:118, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    116     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 118 return fn(*args, **kwargs)

File c:\Users\nl202\miniconda3\envs\py31006th\lib\site-packages\huggingface_hub\file_download.py:1195, in hf_hub_download(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, local_dir, local_dir_use_symlinks, user_agent, force_download, force_filename, proxies, etag_timeout, resume_download, token, local_files_only, legacy_cache_layout)
   1194 try:
-> 1195     metadata = get_hf_file_metadata(
   1196         url=url,
   1197         token=token,
   1198         proxies=proxies,
   1199         timeout=etag_timeout,
   1200     )
   1201 except EntryNotFoundError as http_error:
   1202     # Cache the non-existence of the file and raise

File c:\Users\nl202\miniconda3\envs\py31006th\lib\site-packages\huggingface_hub\utils\_validators.py:118, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    116     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 118 return fn(*args, **kwargs)

File c:\Users\nl202\miniconda3\envs\py31006th\lib\site-packages\huggingface_hub\file_download.py:1541, in get_hf_file_metadata(url, token, proxies, timeout)
   1532 r = _request_wrapper(
   1533     method="HEAD",
   1534     url=url,
   (...)
   1539     timeout=timeout,
   1540 )
-> 1541 hf_raise_for_status(r)
   1543 # Return

File c:\Users\nl202\miniconda3\envs\py31006th\lib\site-packages\huggingface_hub\utils\_errors.py:293, in hf_raise_for_status(response, endpoint_name)
    285     message = (
    286         f"{response.status_code} Client Error."
    287         + "\n\n"
   (...)
    291         " make sure you are authenticated."
    292     )
--> 293     raise RepositoryNotFoundError(message, response) from e
    295 elif response.status_code == 400:

RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-6508609b-66056fe260c0c09f5c752227;a56272fe-4e1b-43fc-b435-e0b47d9222f0)

Repository Not Found for url: https://huggingface.co/None/resolve/main/config.json.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.

The above exception was the direct cause of the following exception:

OSError                                   Traceback (most recent call last)
e:\gdstrm\내 드라이브\Colab Notebooks\dl\dl_nlp\RLHF_3_DPO\2_미디엄블로그\work_미디엄블로그.ipynb Cell 84 line 7
      5 DEV = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
      6 adapter_path = "./model/dpo_results/final_checkpoint"
----> 7 model = AutoPeftModelForCausalLM.from_pretrained(
      8     adapter_path,
      9     torch_dtype=torch.bfloat16,
     10     load_in_4bit=True,
     11     token = HUGGINGFACEHUB_API_TOKEN,
     12 )
     13 tokenizer = AutoTokenizer.from_pretrained(adapter_path)

.............

OSError: None is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'
If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=<your_token>`

请帮助我，如果你知道如何解决错误，谢谢.
※ PS，我使用“facebook/opt-350 m”作为base_model。我忠实地遵循了这个指南（https://github.com/mzbac/llama2-fine-tune）`