Got an error `/data/llama/7B/ does not appear to have a file named config.json. Checkout 'https://huggingface.co//data/llama/7B//None' for available files.` when start a supervised instructs fine-tuning
I have installed https://github.com/hpcaitech/transformers according to the documentation: https://github.com/hpcaitech/ColossalAI/tree/main/applications/Chat#install-the-transformers

- I got an error when I start a supervised instructs fine-tuning

```
(/code/conda-envs) ubuntu@ip-172-31-15-61:/code/valdanito/ColossalAI/applications/Chat/examples$ cat train_sft.sh 
torchrun --standalone --nproc_per_node=4 train_sft.py \
    --pretrain "/data/llama/7B/" \
    --model 'llama' \
    --strategy colossalai_zero2 \
    --log_interval 10 \
    --save_path  /data/coati/7B \
    --dataset /data/coati/data.json \
    --batch_size 4 \
    --accimulation_steps 8 \
    --lr 2e-5 \
    --max_datasets_size 512 \
    --max_epochs 1 \
(/code/conda-envs) ubuntu@ip-172-31-15-61:/code/valdanito/ColossalAI/applications/Chat/examples$ ./train_sft.sh 

```
- Error
```
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /code/valdanito/ColossalAI/applications/Chat/examples/train_sft.py:184 in <module>               │
│                                                                                                  │
│   181 │   parser.add_argument('--lr', type=float, default=5e-6)                                  │
│   182 │   parser.add_argument('--accimulation_steps', type=int, default=8)                       │
│   183 │   args = parser.parse_args()                                                             │
│ ❱ 184 │   train(args)                                                                            │
│   185                                                                                            │
│                                                                                                  │
│ /code/valdanito/ColossalAI/applications/Chat/examples/train_sft.py:50 in train                   │
│                                                                                                  │
│    47 │   │   elif args.model == 'gpt2':                                                         │
│    48 │   │   │   model = GPTLM(pretrained=args.pretrain, lora_rank=args.lora_rank).to(torch.c   │
│    49 │   │   elif args.model == 'llama':                                                        │
│ ❱  50 │   │   │   model = LlamaLM(pretrained=args.pretrain, lora_rank=args.lora_rank,            │
│    51 │   │   │   │   │   │   │   checkpoint=True).to(torch.float16).to(torch.cuda.current_dev   │
│    52 │   │   else:                                                                              │
│    53 │   │   │   raise ValueError(f'Unsupported model "{args.model}"')                          │
│                                                                                                  │
│ /code/conda-envs/lib/python3.10/site-packages/coati/models/llama/llama_lm.py:28 in __init__      │
│                                                                                                  │
│   25 │   │   │   │    lora_train_bias: str = 'none') -> None:                                    │
│   26 │   │                                                                                       │
│   27 │   │   if pretrained is not None:                                                          │
│ ❱ 28 │   │   │   model = LlamaForCausalLM.from_pretrained(pretrained)                            │
│   29 │   │   elif config is not None:                                                            │
│   30 │   │   │   model = LlamaForCausalLM(config)                                                │
│   31 │   │   else:                                                                               │
│                                                                                                  │
│ /code/conda-envs/lib/python3.10/site-packages/transformers/modeling_utils.py:2175 in             │
│ from_pretrained                                                                                  │
│                                                                                                  │
│   2172 │   │   # Load config if we don't provide a configuration                                 │
│   2173 │   │   if not isinstance(config, PretrainedConfig):                                      │
│   2174 │   │   │   config_path = config if config is not None else pretrained_model_name_or_pat  │
│ ❱ 2175 │   │   │   config, model_kwargs = cls.config_class.from_pretrained(                      │
│   2176 │   │   │   │   config_path,                                                              │
│   2177 │   │   │   │   cache_dir=cache_dir,                                                      │
│   2178 │   │   │   │   return_unused_kwargs=True,                                                │
│                                                                                                  │
│ /code/conda-envs/lib/python3.10/site-packages/transformers/configuration_utils.py:546 in         │
│ from_pretrained                                                                                  │
│                                                                                                  │
│   543 │   │   assert config.output_attentions == True                                            │
│   544 │   │   assert unused_kwargs == {"foo": False}                                             │
│   545 │   │   ```"""                                                                             │
│ ❱ 546 │   │   config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwarg   │
│   547 │   │   if "model_type" in config_dict and hasattr(cls, "model_type") and config_dict["m   │
│   548 │   │   │   logger.warning(                                                                │
│   549 │   │   │   │   f"You are using a model of type {config_dict['model_type']} to instantia   │
│                                                                                                  │
│ /code/conda-envs/lib/python3.10/site-packages/transformers/configuration_utils.py:573 in         │
│ get_config_dict                                                                                  │
│                                                                                                  │
│   570 │   │   """                                                                                │
│   571 │   │   original_kwargs = copy.deepcopy(kwargs)                                            │
│   572 │   │   # Get config dict associated with the base config file                             │
│ ❱ 573 │   │   config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwar   │
│   574 │   │   if "_commit_hash" in config_dict:                                                  │
│   575 │   │   │   original_kwargs["_commit_hash"] = config_dict["_commit_hash"]                  │
│   576                                                                                            │
│                                                                                                  │
│ /code/conda-envs/lib/python3.10/site-packages/transformers/configuration_utils.py:628 in         │
│ _get_config_dict                                                                                 │
│                                                                                                  │
│   625 │   │   │                                                                                  │
│   626 │   │   │   try:                                                                           │
│   627 │   │   │   │   # Load from local folder or from cache or download from model Hub and ca   │
│ ❱ 628 │   │   │   │   resolved_config_file = cached_file(                                        │
│   629 │   │   │   │   │   pretrained_model_name_or_path,                                         │
│   630 │   │   │   │   │   configuration_file,                                                    │
│   631 │   │   │   │   │   cache_dir=cache_dir,                                                   │
│                                                                                                  │
│ /code/conda-envs/lib/python3.10/site-packages/transformers/utils/hub.py:380 in cached_file       │
│                                                                                                  │
│    377 │   │   resolved_file = os.path.join(os.path.join(path_or_repo_id, subfolder), filename)  │
│    378 │   │   if not os.path.isfile(resolved_file):                                             │
│    379 │   │   │   if _raise_exceptions_for_missing_entries:                                     │
│ ❱  380 │   │   │   │   raise EnvironmentError(                                                   │
│    381 │   │   │   │   │   f"{path_or_repo_id} does not appear to have a file named {full_filen  │
│    382 │   │   │   │   │   f"'https://huggingface.co/{path_or_repo_id}/{revision}' for availabl  │
│    383 │   │   │   │   )                                                                         │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
OSError: /data/llama/7B/ does not appear to have a file named config.json. Checkout 'https://huggingface.co//data/llama/7B//None' for available files.

```
Sorry, I sent the wrong repo, please close this issue