### What does this PR do?
Type of change: Documentation update
- Update documentation guide for ONNX INT4 PTQ on Windows cuda13 host -
mention about compatible onnxruntim-gpu and cupy-cuda13x packages.
### Testing
- Windows's onnx_ptq\genai_llm INT4 PTQ example with a 1B genai-cuda-ep
ONNX model + local doc building
### Before your PR is "*Ready for review*"
Make sure you read and follow [Contributor
guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md)
and your commits are signed (`git commit -s -S`).
Make sure you read and follow the [Security Best
Practices](https://github.com/NVIDIA/Model-Optimizer/blob/main/SECURITY.md#security-coding-practices-for-contributors)
(e.g. avoiding hardcoded `trust_remote_code=True`, `torch.load(...,
weights_only=False)`, `pickle`, etc.).
- Is this change backward compatible?: ✅ / ❌ / N/A <!--- If ❌, explain
why. -->
- If you copied code from any other sources or added a new PIP
dependency, did you follow guidance in `CONTRIBUTING.md`: ✅ / ❌ / N/A
<!--- Mandatory -->
- Did you write any new necessary tests?: ✅ / ❌ / N/A <!--- Mandatory
for new features or examples. -->
- Did you update
[Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?:
✅ / ❌ / N/A <!--- Only for new features, API changes, critical bug fixes
or backward incompatible changes. -->
- Did you get Claude approval on this PR?: ✅ / ❌ / N/A <!--- Run
`/claude review`. NVIDIA org members can self-trigger for complex
changes; orthogonal to CodeRabbit. -->
### Additional Information
<!-- E.g. related issue. -->
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Documentation**
* Clarified Windows CUDA prerequisites for calibration and
GPU-accelerated quantization.
* Added setup guidance for CUDA 12 and CUDA 13.x, including compatible
packages and cuDNN requirements.
* Expanded installation verification steps for CUDA, ONNX Runtime, and
CuPy.
* Updated the GenAI LLM example with CUDA version compatibility
guidance.
* **Enhancements**
* Added runtime logging of detected CUDA environment paths and version
details during quantization.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: vipandya <vipandya@nvidia.com>
### What does this PR do?
Type of change: ? documentation
<!-- Details about the change. -->
Update windows documentation for onnxruntime quantization with Cuda13.x
### Before your PR is "*Ready for review*"
Make sure you read and follow [Contributor
guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md)
and your commits are signed (`git commit -s -S`).
Make sure you read and follow the [Security Best
Practices](https://github.com/NVIDIA/Model-Optimizer/blob/main/SECURITY.md#security-coding-practices-for-contributors)
(e.g. avoiding hardcoded `trust_remote_code=True`, `torch.load(...,
weights_only=False)`, `pickle`, etc.).
- Is this change backward compatible?: N/A <!--- If ❌, explain why. -->
- If you copied code from any other sources or added a new PIP
dependency, did you follow guidance in `CONTRIBUTING.md`: N/A <!---
Mandatory -->
- Did you write any new necessary tests?: N/A <!--- Mandatory for new
features or examples. -->
- Did you update
[Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?:
N/A <!--- Only for new features, API changes, critical bug fixes or
backward incompatible changes. -->
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Documentation**
* Updated Windows installation guide with CUDA 13.x-specific setup
instructions for GPU-accelerated dependencies, including CuPy and ONNX
Runtime configuration with nightly builds.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: ynankani <ynankani@nvidia.com>
## 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>
### 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.
### Before your PR is "*Ready for review*"
Make sure you read and follow [Contributor
guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md)
and your commits are signed (`git commit -s -S`).
Make sure you read and follow the [Security Best
Practices](https://github.com/NVIDIA/Model-Optimizer/blob/main/SECURITY.md#security-coding-practices-for-contributors)
(e.g. avoiding hardcoded `trust_remote_code=True`, `torch.load(...,
weights_only=False)`, `pickle`, etc.).
- Is this change backward compatible?: ✅ / ❌ / N/A <!--- If ❌, explain
why. -->
- If you copied code from any other sources or added a new PIP
dependency, did you follow guidance in `CONTRIBUTING.md`: ✅ / ❌ / N/A
<!--- Mandatory -->
- Did you write any new necessary tests?: ✅ / ❌ / N/A <!--- Mandatory
for new features or examples. -->
- Did you update
[Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?:
✅ / ❌ / N/A <!--- Only for new features, API changes, critical bug fixes
or backward incompatible changes. -->
### Additional Information
<!-- E.g. related issue. -->
<!-- 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>
## What does this PR do?
Documentation
**Overview:**
- Update support matrix, changelog, deployment page, example readmes as
per recent feature and model support on Windows side.
## Testing
- No testing, its just documentation change
## Before your PR is "*Ready for review*"
<!-- If you haven't finished some of the above items you can still open
`Draft` PR. -->
- **Make sure you read and follow [Contributor
guidelines](https://github.com/NVIDIA/Model-Optimizer/blob/main/CONTRIBUTING.md)**
and your commits are signed.
- **Is this change backward compatible?**: Yes/No <!--- If No, explain
why. -->
- **Did you write any new necessary tests?**: Yes/No
- **Did you add or update any necessary documentation?**: Yes/No
- **Did you update
[Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?**:
Yes/No <!--- Only for new features, API changes, critical bug fixes or
bw breaking changes. -->
## Additional Information
<!-- E.g. related issue. -->
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **New Features**
* Added ONNX Mixed Precision Weight-only quantization (INT4/INT8)
support.
* Introduced diffusion-model quantization on Windows.
* Added new accuracy benchmarks (Perplexity and KL-Divergence).
* Expanded deployment with multiple ONNX Runtime Execution Providers
(CUDA, DirectML, TensorRT-RTX).
* **Bug Fixes**
* Fixed ONNX 1.19 compatibility issue with CuPy during INT4 AWQ
quantization.
* **Documentation**
* Updated installation guides with system requirements and multiple
backend options.
* Reorganized deployment documentation with comprehensive execution
provider guidance.
* Expanded example workflows with improved setup instructions and
support matrices.
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: vipandya <vipandya@nvidia.com>
- [x] Product Rename: TensorRT Model Optimizer to Model Optimizer
(OMNIML-3033)
- [x] Mention in Latest News section with date on the date of merging
this PR (12/08)
Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>