Update README.md

README.md

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 Phi-mini-MoE is a lightweight Mixture of Experts (MoE) model with 7.6B total parameters and 2.4B activated parameters. It is compressed and distilled from the base model shared by [Phi-3.5-MoE](https://huggingface.co/microsoft/Phi-3.5-MoE-instruct) and [GRIN-MoE](https://huggingface.co/microsoft/GRIN-MoE) using the [SlimMoE](https://arxiv.org/pdf/2506.18349) approach, then post-trained via supervised fine-tuning and direct preference optimization for instruction following and safety. The model is trained on Phi-3 synthetic data and filtered public documents, with a focus on high-quality, reasoning-dense content. It is part of the SlimMoE series, which includes a smaller variant, [Phi-tiny-MoE](https://huggingface.co/microsoft/Phi-tiny-MoE-instruct), with 3.8B total and 1.1B activated parameters.
 
-Project Page: https://huggingface.co/microsoft/Phi-mini-MoE-instruct
-Code: https://github.com/microsoft/LMOps/tree/main/src/moe
-
 References: <br>
 📖 [SlimMoE](https://arxiv.org/pdf/2506.18349) <br>
 📖 [Phi-3 Technical Report](https://arxiv.org/abs/2404.14219) <br>