Update README.md

README.md

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 Qwen1.5-MoE is a transformer-based MoE decoder-only language model pretrained on a large amount of data. 
 
-For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen1.5-moe/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5).
+For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen-moe/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5).
 
 ## Model Details
 Qwen1.5-MoE employs Mixture of Experts (MoE) architecture, where the models are upcycled from dense language models. For instance, `Qwen1.5-MoE-A2.7B` is upcycled from `Qwen-1.8B`. It has 14.3B parameters in total and 2.7B activated parameters during runtime, while achieching comparable performance to `Qwen1.5-7B`, it only requires 25% of the training resources. We also observed that the inference speed is 1.74 times that of `Qwen1.5-7B`.