Using nemo LM in other nemo training 
I want to use our own training nemo LM in other nemo training and  I found only this  reference  [https://github.com/NVIDIA/NeMo/blob/4cd9b3449cbfedc671348fbabbe8e3a55fbd659d/examples/nlp/text_classification/conf/ptune_text_classification_config.yaml](url) that have nemo_path in language model config

so I follow that(training text classification) but it doesn't work, it has to have model.tokenizer.tokenizer_name

> [NeMo I 2022-12-20 16:02:14 exp_manager:563] TensorboardLogger has been set up
> Traceback (most recent call last):
>   File "/workspace/data/bew/NeMo/examples/nlp/text_classification/text_classification_with_bert.py", line 117, in main
>     model = TextClassificationModel(cfg.model, trainer=trainer)
>   File "/opt/conda/lib/python3.8/site-packages/nemo/collections/nlp/models/text_classification/text_classification_model.py", line 54, in __init__
>     self.setup_tokenizer(cfg.tokenizer)
>   File "/opt/conda/lib/python3.8/site-packages/nemo/collections/nlp/models/nlp_model.py", line 112, in setup_tokenizer
>     tokenizer_name=cfg.tokenizer_name,
> omegaconf.errors.ConfigAttributeError: Key 'tokenizer_name' is not in struct
>         full_key: model.tokenizer.tokenizer_name
>         reference_type=Any
>         object_type=dict
> 
> Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

If I mention model.tokenizer.tokenizer_name and model.language_model.pretrained_model_name then put model.language_model.nemo_file(path to our custom nemo model), the training look ok but it seems to use the model from huggingface.

Is there a way to using custom LM model? 