How to use model after transfer learning on new dataset
Hi,
Used `quartznet_15x5` model for the transfer learning on the open-source dataset (AN4 dataset) for ASR. Once the pre-trained model gets trained with the newer dataset. I tried saving the trained model. Once I tested with the saved model using `nemo_asr.models.<MODEL_BASE_CLASS>.restore_from(restore_path="<path/to/checkpoint/file.nemo>")`. It shows the empty result `[' ']` even on the trained data.

Kindly provide us with the steps to follow after the transfer learning progress.

Code: 
```
config_path = './quartznet_15x5.yaml'

yaml = YAML(typ='safe')
with open(config_path) as f:
    params = yaml.load(f)

trainer = pl.Trainer(gpus=1, max_epochs=50)
quartznet_model = nemo_asr.models.EncDecCTCModel(cfg=DictConfig(params['model']), trainer=trainer)

trainer.fit(quartznet_model)
quartznet_model.save_to("./tl-osd.nemo")

```