runtime error

Space failed. Exit code: 1. Reason: 10/site-packages/huggingface_hub/utils/_validators.py", line 118, in _inner_fn return fn(*args, **kwargs) File "/home/user/.local/lib/python3.10/site-packages/huggingface_hub/file_download.py", line 1608, in get_hf_file_metadata hf_raise_for_status(r) File "/home/user/.local/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py", line 293, in hf_raise_for_status raise RepositoryNotFoundError(message, response) from e huggingface_hub.utils._errors.RepositoryNotFoundError: 401 Client Error. (Request ID: Root=1-654dd921-472daa701af191ad762c8a59;52027cb2-f594-45fd-9933-1d8635ec0425) Repository Not Found for url: https://huggingface.co./SeyedAli/Persian-Image-Captioning-VIT-GPT/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. Invalid username or password. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/user/app/app.py", line 9, in <module> model = VisionEncoderDecoderModel.from_pretrained("SeyedAli/Persian-Image-Captioning-VIT-GPT") File "/home/user/.local/lib/python3.10/site-packages/transformers/models/vision_encoder_decoder/modeling_vision_encoder_decoder.py", line 363, in from_pretrained return super().from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) File "/home/user/.local/lib/python3.10/site-packages/transformers/modeling_utils.py", line 2507, in from_pretrained resolved_config_file = cached_file( File "/home/user/.local/lib/python3.10/site-packages/transformers/utils/hub.py", line 450, in cached_file raise EnvironmentError( OSError: SeyedAli/Persian-Image-Captioning-VIT-GPT 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>`

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