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skyw merged 1 commit into from
Jun 23, 2026
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Update readme #232

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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -60,11 +60,11 @@ Refer to tests for usage of different optimizers, e.g. [`tests/test_orthogonali

### Integration with Megatron Core

Integration with Megatron Core is available in **dev** branch, e.g. [emerging_optimizers.py](https://github.com/NVIDIA/Megatron-LM/blob/dev/megatron/core/optimizer/emerging_optimizers.py)
Emerging optimizer has been integrated into Megatron Core with tensor parallel support and many other features (split QKV for example), check out [emerging_optimizers.py](https://github.com/NVIDIA/Megatron-LM/blob/core_v0.18.0/megatron/core/optimizer/emerging_optimizers.py).

@greptile-apps greptile-apps Bot Jun 23, 2026

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P2 Minor subject–verb agreement: the project is consistently referred to as "Emerging Optimizers" (plural) throughout the README, but this sentence opens with the singular "Emerging optimizer".

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Emerging optimizer has been integrated into Megatron Core with tensor parallel support and many other features (split QKV for example), check out [emerging_optimizers.py](https://github.com/NVIDIA/Megatron-LM/blob/core_v0.18.0/megatron/core/optimizer/emerging_optimizers.py).
Emerging optimizers have been integrated into Megatron Core with tensor parallel support and many other features (split QKV for example), check out [emerging_optimizers.py](https://github.com/NVIDIA/Megatron-LM/blob/core_v0.18.0/megatron/core/optimizer/emerging_optimizers.py).

Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!


## Benchmarks

Coming soon.
Benchmark of Muon can be found in our [blog](https://developer.nvidia.com/blog/advancing-emerging-optimizers-for-accelerated-llm-training-with-nvidia-megatron/).

## License

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