Minor Doc updates

Signed-off-by: Keval Morabia <[email protected]>

Author: kevalmorabia97

README.md

@@ -75,8 +75,10 @@ pip install -e .[dev]
 ```
 
 You can also directly use the [TensorRT-LLM docker images](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags)
-(e.g., `nvcr.io/nvidia/tensorrt-llm/release:<version>`),
-which have Model Optimizer pre-installed. Visit our [installation guide](https://nvidia.github.io/TensorRT-Model-Optimizer/getting_started/2_installation.html) for more fine-grained control on installed dependencies or for alternative docker images and environment variables to setup.
+(e.g., `nvcr.io/nvidia/tensorrt-llm/release:<version>`), which have Model Optimizer pre-installed.
+Make sure to upgrade Model Optimizer to the latest version using ``pip`` as described above.
+Visit our [installation guide](https://nvidia.github.io/TensorRT-Model-Optimizer/getting_started/2_installation.html) for
+more fine-grained control on installed dependencies or for alternative docker images and environment variables to setup.
 
 ## Techniques
 

docs/source/getting_started/_installation_for_Linux.rst

@@ -34,7 +34,7 @@ Environment setup
     `TensorRT-LLM docker image <https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/release/tags>`_,
     e.g., ``nvcr.io/nvidia/tensorrt-llm/release:<version>``.
 
-    You may upgrade the Model Optimizer to the latest version if not already as described in the next section.
+    Make sure to upgrade Model Optimizer to the latest version using ``pip`` as described in the next section.
 
     You would also need to setup appropriate environment variables for the TensorRT binaries as follows: