Files
Model-Optimizer/tests/_test_utils/torch/export
Frida Hou dfe705aab5 support static NVFP4 HF export (#858)
## What does this PR do?

**Type of change:** ? new feature

**Overview:** ?
Supports export `NVFP4StaticQantizer` in unified huggingface checkpoint,
as a deployment path for PTQ algorithms such as MSE

## Usage
<!-- You can potentially add a usage example below. -->

```python
# checkpoint generation
python examples/llm_ptq/hf_ptq.py --pyt_ckpt_path Qwen/Qwen3-8B  --qformat nvfp4_mse --export_path test-Qwen3-8B-Instruct-MSE-FP8-sweep-FP4 --kv_cache_qformat none --trust_remote_code 

```

## Testing
Tested generated Qwen3 8B checkpoint with trtllm serve and nv_eval
example in `Model-Optimizer-Internal/examples/nv_eval`.

NV eval results:
```
| Groups |Version|Filter|n-shot|  Metric   |   |Value |   |Stderr|
|--------|-------|------|------|-----------|---|-----:|---|-----:|
|mmlu_str|       |none  |      |exact_match|↑  |0.7186|±  |0.0036|
```


## 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 support for static NVFP4 quantizers that utilize pre-computed
calibration scales.
* Introduced new NVFP4 W4A4 quantization configuration with optional FP8
scale sweep.

* **Performance Improvements**
* Static quantizers now skip unnecessary dynamic scaling factor
recalculation.
* Unified quantization handling for improved consistency and efficiency.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: Fridah-nv <201670829+Fridah-nv@users.noreply.github.com>
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
2026-02-26 10:41:29 -08:00
..
2026-02-26 10:41:29 -08:00