docs: update installation pages with legal-approved license notices (#1322)

## Summary

- Replaces the old pip license notice ("Please review the license terms
of ModelOpt and any dependencies before use") with the Legal-approved
wording: "Model Optimizer will download and install additional
third-party open source software projects. Review the license terms of
these open source projects before use."
- Adds a generic container license review notice ("Before pulling and
using the container images, please review their respective license
terms.") to the Linux installation doc (Docker tab) and README.
- Adds a `.. note::` with the pip notice to the Windows installation
page (covers both standalone and Olive child pages).
- Expands the README container section to explicitly list all four
recommended NVIDIA container images (`pytorch`, `nemo`, `tensorrt-llm`,
`tensorrt`).

## Test plan

- [x] Verify rendered docs look correct (`nox -s docs`)
- [x] Confirm legal notices appear in Linux, Windows, and README install
sections

🤖 Generated with [Claude Code](https://claude.com/claude-code)

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **Documentation**
* Updated installation guides with explicit references to supported
NVIDIA container images (PyTorch, NeMo, TensorRT-LLM and variants),
clarified pre-installed Model Optimizer in some images, and added notes
to review each container’s license terms; clarified conditional
environment setup wording and local install license guidance.
* **Chores**
  * Updated project license header year.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

LICENSE_HEADER

@@ -1,4 +1,4 @@
-SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 SPDX-License-Identifier: Apache-2.0
 
 Licensed under the Apache License, Version 2.0 (the "License");

README.md

@@ -69,6 +69,8 @@ To install stable release packages for Model Optimizer with `pip` from [PyPI](ht
 pip install -U nvidia-modelopt[all]
 ```
 
+Model Optimizer will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.
+
 To install from source in editable mode with all development dependencies or to use the latest features, run:
 
 ```bash
@@ -79,8 +81,14 @@ cd Model-Optimizer
 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.
+You can also directly use NVIDIA container images, which have Model Optimizer pre-installed:
+
+- `nvcr.io/nvidia/pytorch:<version>-py3`
+- `nvcr.io/nvidia/nemo:<version>`
+- `nvcr.io/nvidia/tensorrt-llm/release:<version>`
+- `nvcr.io/nvidia/tensorrt:<version>-py3`
+
+Before pulling and using the container images, please review their respective license terms.
 Make sure to upgrade Model Optimizer to the latest version as described above.
 Visit our [installation guide](https://nvidia.github.io/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.

docs/source/getting_started/_installation_for_Linux.rst

@@ -32,11 +32,11 @@ Environment setup
 
     To use Model Optimizer with full dependencies (e.g. TensorRT/TensorRT-LLM deployment), we recommend using the
     `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>``.
+    e.g., ``nvcr.io/nvidia/tensorrt-llm/release:<version>`` (Model Optimizer pre-installed).
 
     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:
+    If relevant, you would also need to setup appropriate environment variables for the TensorRT binaries as follows:
 
     .. code-block:: shell
 
@@ -48,11 +48,16 @@ Environment setup
     **Alternative NVIDIA docker images**
 
     For PyTorch, you can also use `NVIDIA NGC PyTorch container <https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch/tags>`_
-    and for NVIDIA Megatron-Bridge or Megatron-LM framework, you can use the `NeMo container <https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo/tags>`_.
-    Both of these containers come with Model Optimizer pre-installed. Make sure to update the Model Optimizer to the latest version if not already.
+    (``nvcr.io/nvidia/pytorch:<version>-py3``, Model Optimizer pre-installed)
+    and for NVIDIA Megatron-Bridge or Megatron-LM framework, you can use the `NeMo container <https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo/tags>`_
+    (``nvcr.io/nvidia/nemo:<version>``, Model Optimizer pre-installed).
+    Make sure to update the Model Optimizer to the latest version if not already.
 
     For ONNX / TensorRT use cases, you can also use the `TensorRT container <https://catalog.ngc.nvidia.com/orgs/nvidia/containers/tensorrt/tags>`_
-    which provides superior performance to the PyTorch container.
+    (``nvcr.io/nvidia/tensorrt:<version>-py3``), which provides superior performance to the PyTorch container.
+
+    .. note::
+        Before pulling and using the container images, please review their respective license terms.
 
 .. tab:: Local environment (PIP / Conda)
 
@@ -82,8 +87,8 @@ Environment setup
 Install Model Optimizer
 =======================
 
-ModelOpt including its dependencies can be installed via ``pip``. Please review the license terms of ModelOpt and any
-dependencies before use.
+Model Optimizer will download and install additional third-party open source software projects. Review the license
+terms of these open source projects before use.
 
 If you build and use ModelOpt's docker image, you can skip this step as the image already contains ModelOpt and all
 optional dependencies pre-installed.

docs/source/getting_started/windows/_installation_for_Windows.rst

@@ -30,6 +30,10 @@ The following system requirements are necessary to install and use Model Optimiz
 
 The Model Optimizer - Windows can be used in following ways:
 
+.. note::
+   Model Optimizer will download and install additional third-party open source software projects.
+   Review the license terms of these open source projects before use.
+
 .. toctree::
    :glob:
    :maxdepth: 1