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The above piece of code works for me. However, if I change the cache dir to be "EleutherAI/pythia-12b", the bin files are not downloaded, and the code errors. Shouldn't it work irrespective of what the cache_dir is?
File [/mnt/align4_drive/arunas/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/modeling_utils.py:3075](http://localhost:8001/lab/tree/rm-interp/rm-playground/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/modeling_utils.py#line=3074), in PreTrainedModel.from_pretrained(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, *model_args, **kwargs)
3073 if not isinstance(config, PretrainedConfig):
3074 config_path = config if config is not None else pretrained_model_name_or_path
-> 3075 config, model_kwargs = cls.config_class.from_pretrained(
3076 config_path,
3077 cache_dir=cache_dir,
3078 return_unused_kwargs=True,
3079 force_download=force_download,
3080 resume_download=resume_download,
3081 proxies=proxies,
3082 local_files_only=local_files_only,
3083 token=token,
3084 revision=revision,
3085 subfolder=subfolder,
3086 _from_auto=from_auto_class,
3087 _from_pipeline=from_pipeline,
3088 **kwargs,
3089 )
3090 else:
3091 # In case one passes a config to `from_pretrained` + "attn_implementation"
3092 # override the `_attn_implementation` attribute to `attn_implementation` of the kwargs
(...)
3096 # we pop attn_implementation from the kwargs but this handles the case where users
3097 # passes manually the config to `from_pretrained`.
3098 config = copy.deepcopy(config)
File [/mnt/align4_drive/arunas/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/configuration_utils.py:605](http://localhost:8001/lab/tree/rm-interp/rm-playground/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/configuration_utils.py#line=604), in PretrainedConfig.from_pretrained(cls, pretrained_model_name_or_path, cache_dir, force_download, local_files_only, token, revision, **kwargs)
601 kwargs["revision"] = revision
603 cls._set_token_in_kwargs(kwargs, token)
--> 605 config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs)
606 if "model_type" in config_dict and hasattr(cls, "model_type") and config_dict["model_type"] != cls.model_type:
607 logger.warning(
608 f"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
609 f"{cls.model_type}. This is not supported for all configurations of models and can yield errors."
610 )
File [/mnt/align4_drive/arunas/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/configuration_utils.py:634](http://localhost:8001/lab/tree/rm-interp/rm-playground/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/configuration_utils.py#line=633), in PretrainedConfig.get_config_dict(cls, pretrained_model_name_or_path, **kwargs)
632 original_kwargs = copy.deepcopy(kwargs)
633 # Get config dict associated with the base config file
--> 634 config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
635 if "_commit_hash" in config_dict:
636 original_kwargs["_commit_hash"] = config_dict["_commit_hash"]
File [/mnt/align4_drive/arunas/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/configuration_utils.py:689](http://localhost:8001/lab/tree/rm-interp/rm-playground/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/configuration_utils.py#line=688), in PretrainedConfig._get_config_dict(cls, pretrained_model_name_or_path, **kwargs)
685 configuration_file = kwargs.pop("_configuration_file", CONFIG_NAME)
687 try:
688 # Load from local folder or from cache or download from model Hub and cache
--> 689 resolved_config_file = cached_file(
690 pretrained_model_name_or_path,
691 configuration_file,
692 cache_dir=cache_dir,
693 force_download=force_download,
694 proxies=proxies,
695 resume_download=resume_download,
696 local_files_only=local_files_only,
697 token=token,
698 user_agent=user_agent,
699 revision=revision,
700 subfolder=subfolder,
701 _commit_hash=commit_hash,
702 )
703 commit_hash = extract_commit_hash(resolved_config_file, commit_hash)
704 except EnvironmentError:
705 # Raise any environment error raise by `cached_file`. It will have a helpful error message adapted to
706 # the original exception.
File [/mnt/align4_drive/arunas/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/utils/hub.py:356](http://localhost:8001/lab/tree/rm-interp/rm-playground/miniconda3/envs/rm-score/lib/python3.11/site-packages/transformers/utils/hub.py#line=355), 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)
354 if not os.path.isfile(resolved_file):
355 if _raise_exceptions_for_missing_entries:
--> 356 raise EnvironmentError(
357 f"{path_or_repo_id} does not appear to have a file named {full_filename}. Checkout "
358 f"'https://huggingface.co/{path_or_repo_id}/{[revision](https://huggingface.co/%7Bpath_or_repo_id%7D/%7Brevision)}' for available files."
359 )
360 else:
361 return None
OSError: EleutherAI[/pythia-12b](http://localhost:8001/pythia-12b) does not appear to have a file named config.json. Checkout 'https://huggingface.co/EleutherAI/pythia-12b/step143000' for available files.
```
The text was updated successfully, but these errors were encountered:
The above piece of code works for me. However, if I change the cache dir to be "EleutherAI/pythia-12b", the bin files are not downloaded, and the code errors. Shouldn't it work irrespective of what the cache_dir is?
Error Trace:
``` --------------------------------------------------------------------------- OSError Traceback (most recent call last) Cell In[30], line 3 1 from transformers import GPTNeoXForCausalLM, AutoTokenizer ----> 3 model = GPTNeoXForCausalLM.from_pretrained( 4 "EleutherAI[/pythia-12b](http://localhost:8001/pythia-12b)", 5 revision="step143000", 6 cache_dir="EleutherAI[/pythia-12b](http://localhost:8001/pythia-12b)" 7 ) 9 tokenizer = AutoTokenizer.from_pretrained( 10 "EleutherAI[/pythia-12b](http://localhost:8001/pythia-12b)", 11 cache_dir="EleutherAI[/pythia-12b](http://localhost:8001/pythia-12b)" 12 ) 14 inputs = tokenizer("Hello, I am", return_tensors="pt")The text was updated successfully, but these errors were encountered: