LiLT
LiLT copied to clipboard
Config error in Multi-task Semantic Entity Recognition on XFUND
I am getting errors when trying to run Multi-task Semantic Entity Recognition on XFUND by following the instructions in the README. Specifically, the config initialisation on line 127 in run_xfun_ser.py
is failing with the following error:
Traceback (most recent call last):
File "/opt/conda/lib/python3.8/site-packages/transformers/configuration_utils.py", line 546, in get_config_dict
resolved_config_file = cached_path(
File "/opt/conda/lib/python3.8/site-packages/transformers/file_utils.py", line 1402, in cached_path
output_path = get_from_cache(
File "/opt/conda/lib/python3.8/site-packages/transformers/file_utils.py", line 1574, in get_from_cache
r.raise_for_status()
File "/opt/conda/lib/python3.8/site-packages/requests/models.py", line 1021, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 401 Client Error: Unauthorized for url: https://huggingface.co/lilt-infoxlm-base/resolve/main/config.json
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/opt/conda/lib/python3.8/site-packages/transformers/models/auto/configuration_auto.py", line 527, in from_pretrained
config_dict, _ = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/transformers/configuration_utils.py", line 570, in get_config_dict
raise EnvironmentError(msg)
OSError: Can't load config for 'lilt-infoxlm-base'. Make sure that:
- 'lilt-infoxlm-base' is a correct model identifier listed on 'https://huggingface.co/models'
- or 'lilt-infoxlm-base' is the correct path to a directory containing a config.json file
- or 'main' is a valid git identifier (branch name, a tag name, or a commit id) that exists for this model name as listed on its model page on 'https://huggingface.co/models'
I have also tried to download the model from the provided OneCloud link and point the config_name
argument to the config.json
contained within the compressed file, however I am getting another error in that case:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/opt/conda/lib/python3.8/site-packages/transformers/models/auto/configuration_auto.py", line 529, in from_pretrained
config_class = CONFIG_MAPPING[config_dict["model_type"]]
File "/opt/conda/lib/python3.8/site-packages/transformers/models/auto/configuration_auto.py", line 278, in __getitem__
raise KeyError(key)
KeyError: 'liltrobertalike'
I had to change the init file and update the requirements as I was facing the same problem as in issue #32. The updated versions are:
datasets==2.7.1
transformers==4.11.3
Did something change or am I doing something wrong?