message: Modified the notebooks directory's README file. Updated the repo's origin and the example container tag. Also split up the docker run commands across several lines to improve legibility.
diff: @@ -8,7 +8,7 @@ The most convenient way to run these notebooks is via a docker container, which
  First, clone the repository:
  ```
  -git clone https://github.com/NVIDIA/Torch-TensorRT
  +git clone https://github.com/pytorch/TensorRT
  ```
  Next, navigate to the repo's root directory:
  @@ -23,10 +23,10 @@ At this point, we recommend pulling the [PyTorch container](https://catalog.ngc.
  from [NVIDIA GPU Cloud](https://catalog.ngc.nvidia.com/) as follows:
  ```
  -docker pull nvcr.io/nvidia/pytorch:21.12-py3
  +docker pull nvcr.io/nvidia/pytorch:22.05-py3
  ```
  -Replace ```21.12``` with a different string in the form ```yy.mm```,
  +Replace ```22.05``` with a different string in the form ```yy.mm```,
  where ```yy``` indicates the last two numbers of a calendar year, and
  ```mm``` indicates the month in two-digit numerical form, if you wish
  to pull a different version of the container.
  @@ -36,14 +36,18 @@ Therefore, you can run the container and the notebooks therein without
  mounting the repo to the container. To do so, run
  ```
  -docker run --gpus=all --rm -it --net=host --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/pytorch:21.12-py3 bash
  +docker run --gpus=all --rm -it --net=host --ipc=host \
  +--ulimit memlock=-1 --ulimit stack=67108864 \
  +nvcr.io/nvidia/pytorch:22.05-py3 bash
  ```
  If, however, you wish for your work in the notebooks to persist, use the
  ```-v``` flag to mount the repo to the container as follows:
  ```
  -docker run --gpus=all --rm -it -v $PWD:/Torch-TensorRT --net=host --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 nvcr.io/nvidia/pytorch:21.12-py3 bash
  +docker run --gpus=all --rm -it -v $PWD:/Torch-TensorRT \
  +--net=host --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \
  +nvcr.io/nvidia/pytorch:22.05-py3 bash
  ```
  ### b. Building a Torch-TensorRT container from source
  @@ -57,7 +61,9 @@ docker build -t torch_tensorrt -f ./docker/Dockerfile .
  To run this container, enter the following command:
  ```
  -docker run --gpus=all --rm -it -v $PWD:/Torch-TensorRT --net=host --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 torch_tensorrt:latest bash
  +docker run --gpus=all --rm -it -v $PWD:/Torch-TensorRT \
  +--net=host --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \
  +torch_tensorrt:latest bash
  ```
  ### c. Running the notebooks inside the container
  @@ -100,8 +106,3 @@ Within the container, the notebooks themselves are located at `/Torch-TensorRT/n
  - [vgg-qat.ipynb](vgg-qat.ipynb): Quantization Aware Trained models in INT8 using Torch-TensorRT
  - [EfficientNet-example.ipynb](EfficientNet-example.ipynb): Simple use of 3rd party PyTorch model library
  - [CitriNet-example.ipynb](CitriNet-example.ipynb): Optimizing the Nemo Citrinet acoustic model
  -
  -
  -```python
  -
  -```
  