Token_Classification_Named_Entity_Recognition.ipynb specifies specific gpu instead of a single gpu
**Describe the bug**

In the notebook [Token_Classification_Named_Entity_Recognition.ipynb](https://github.com/NVIDIA/NeMo/blob/main/tutorials/nlp/Token_Classification_Named_Entity_Recognition.ipynb), the last cell specifies a specific gpu, which happens to be the second gpu, when it most likely was meant to specify a single gpu.  This causes an error if only one gpu is present on the system.<br>
The error is:
```
MisconfigurationException: 
                You requested GPUs: [1]
                But your machine only has: [0]
```

**Steps/Code to reproduce bug**

Set up a single-GPU box with the v1.0.0b3 version of NeMo running in a container
Upload the [notebook](https://github.com/NVIDIA/NeMo/blob/main/tutorials/nlp/Token_Classification_Named_Entity_Recognition.ipynb)
Run all the cells.

**Expected behavior**

no error when running a single GPU

**Proposed fix for the bug**

In the final cell of the [notebook](https://github.com/NVIDIA/NeMo/blob/main/tutorials/nlp/Token_Classification_Named_Entity_Recognition.ipynb), we see the following:<br>
`trainer = pl.Trainer(gpus=[1], fast_dev_run=fast_dev_run)`<br>
I believe the intent was to run on a only one GPU, but instead we are saying GPU No. 1, which is generally the second GPU in a system where the first GPU is GPU No. 0.  We get an error when there is only one GPU.  To run on a single GPU, the line should be:<br>
`trainer = pl.Trainer(gpus=1, fast_dev_run=fast_dev_run)`<br>

This is explained in the [PyTorch Lighnting gpus documentation](https://pytorch-lightning.readthedocs.io/en/latest/trainer.html#gpus).

**Environment overview (please complete the following information)**

 - Environment location: Docker on AWS V100
 - Method of NeMo install: Docker
 - If method of install is [Docker], provide `docker pull` & `docker run` commands used
    pulled from `nvcr.io/nvidian/nemo/nemo:1.0.0b3`

