Update ModelOpt-with-Olive documentation to mention CUDA EP commands (#1099)

### What does this PR do?

Type of change: Minor documentation update

- Update documentation (olive installation instructions) to mention
install commands for CUDA EP packages for ORT / ORT-genai.

### Testing

- Locally checked the readme, doc.

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

* **Documentation**
* Updated Windows Olive installation guidance to recommend CUDA-based
ONNX Runtime packages instead of DirectML and added a link to ONNX
Runtime’s Execution-Provider docs for alternative EPs and requirements.
* Simplified Windows examples by removing explicit package install
commands and pointing users to the consolidated Olive setup
instructions.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: vipandya <vipandya@nvidia.com>

Author: vishalpandya1990

docs/source/getting_started/windows/_installation_with_olive.rst

@@ -17,14 +17,16 @@ Setup Steps for Olive with ModelOpt-Windows
 
          pip install olive-ai[nvmo]
 
-   - **Install Prerequisites:** Ensure all required dependencies are installed. For example, to use DirectML Execution-Provider (EP) based onnxruntime and onnxruntime-genai packages, run the following commands:
+   - **Install Prerequisites:** Ensure all required dependencies are installed. For example, to install CUDA Execution-Provider (EP) based onnxruntime and onnxruntime-genai packages, run the following commands:
 
      .. code-block:: shell
 
-            $ pip install onnxruntime-genai-directml>=0.4.0
-            $ pip install onnxruntime-directml==1.20.0
+            $ pip install onnxruntime-genai-cuda
+            $ pip install onnxruntime-gpu
 
-   - Above onnxruntime and onnxruntime-genai packages enable Olive workflow with DirectML Execution-Provider (EP). To use other EPs, install corresponding packages.
+   - Above onnxruntime and onnxruntime-genai packages enable Olive workflow with CUDA Execution-Provider (EP). To use other EPs, install corresponding packages.
+
+   - Refer to the ONNX Runtime's `EP documentation <https://onnxruntime.ai/docs/execution-providers/>`_ for details about different EPs, their requirements, and installation instructions.
 
    - Additionally, ensure that dependencies for Model Optimizer - Windows are met as mentioned in the :ref:`Install-Page-Standalone-Windows`.
 

examples/windows/README.md

@@ -51,15 +51,14 @@ pip install nvidia-modelopt[onnx]
 
 ### Installation with Olive
 
-To install ModelOpt-Windows through Microsoft's Olive, use the following commands:
+The ModelOpt-Windows is integrated into Microsoft's [Olive](https://microsoft.github.io/Olive/) framework. Run the following commands to install ModelOpt through Olive.
 
 ```bash
 pip install olive-ai[nvmo]
-pip install onnxruntime-genai-directml>=0.4.0
-pip install onnxruntime-directml==1.20.0
+pip install onnxruntime-genai-cuda
 ```
 
-For more details, please refer to the [detailed installation instructions](https://nvidia.github.io/Model-Optimizer/getting_started/windows/_installation_for_Windows.html).
+For more details, or to use different [ONNX Runtime Execution Providers](https://onnxruntime.ai/docs/execution-providers/), refer to the [detailed installation instructions](https://nvidia.github.io/Model-Optimizer/getting_started/windows/_installation_for_Windows.html).
 
 ## Techniques