TransformerLMModel loads tokenizer from the local file instead of .nemo trained file
This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days. This issue was closed because it has been inactive for 7 days since being marked as stale.
**TransformerLMModel loads tokenizer from the local file instead of .nemo trained file**

While using `TransformerLMModel.restore_from(<.nemo file>)`, the tokenizer is loaded from the local tokenizers file instead of the tokenizer found in the `.nemo` model file.

As shown in the snippet below from [nemo/collections/nlp/models/language_modeling/transformer_lm_model.py](https://github.com/NVIDIA/NeMo/blob/0b7467ebd158ef6876dd147189517b25ef626982/nemo/collections/nlp/models/language_modeling/transformer_lm_model.py#L57), the models uses `tokenizer_model` instead of `cfg.tokenizer.tokenizer_model` to load the tokenizer, which refers to the path to the local tokenizer.
This implementation is causing an issue when I try to load the model in another location other than where it's trained from.

```python
self.setup_tokenizer(
            tokenizer_name=cfg.tokenizer.get("tokenizer_name", "yttm"),
            tokenizer_model=cfg.tokenizer.get("tokenizer_model", None),
            vocab_file=cfg.tokenizer.get("vocab_file", None),
            bpe_dropout=cfg.tokenizer.get("bpe_dropout", 0.0),
            special_tokens=OmegaConf.to_container(cfg.tokenizer.special_tokens)
            if cfg.tokenizer.get("special_tokens", None)
            else None,
        )
```
