Model-Optimizer

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Chenjie Luo a4fde491cc Update MOE block detection logic and enable in huggingface_script.sh (#962 )

### What does this PR do?

Type of change: Bug fix

Add moe expert calib ratio in huggingface_script.sh
Also fix minimax2.5 MOE detection which does not follow other HF MOE
layer convention

### Usage

scripts/huggingface_example.sh --model <MiniMax-M2.5> --quant nvfp4
--moe_calib_experts_ratio 1.0 --trust_remote_code

### Before your PR is "*Ready for review*"

Make sure you read and follow [Contributor
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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`, using
`torch.load(..., weights_only=True)`, avoiding `pickle`, etc.).

- Is this change backward compatible?: ✅ / ❌ / N/A <!--- If ❌, explain
why. -->
- If you copied code from any other source, did you follow IP policy in
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for new features or examples. -->
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[Changelog](https://github.com/NVIDIA/Model-Optimizer/blob/main/CHANGELOG.rst)?:
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### Additional Information
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<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **New Features**
* Configure MOE calibration experts ratio for quantization via an
environment/option, enabling finer control over calibration.

* **Bug Fixes**
* Improved detection of sparse MOE blocks to handle varying
expert/topology layouts, inferring expert counts when needed for more
reliable processing.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: Chenjie Luo <chenjiel@nvidia.com>