Update SGLang installation and documentation links (#3422)

Update SGLang installation and documentation links
Fix `File not found` for SGLang related links

Author: Bobchenyx

README.md

@@ -321,12 +321,12 @@ vLLM occasionally differs in output from Huggingface. We treat Huggingface as th
 
 We support SGLang for efficient offline batch inference. Its **[Fast Backend Runtime](https://docs.sglang.ai/index.html)** delivers high performance through optimized memory management and parallel processing techniques. Key features include tensor parallelism, continuous batching, and support for various quantization methods (FP8/INT4/AWQ/GPTQ).
 
-To use SGLang as the evaluation backend, please **install it in advance** via SGLang documents [here](https://docs.sglang.ai/start/install.html#install-sglang).
+To use SGLang as the evaluation backend, please **install it in advance** via SGLang documents [here](https://docs.sglang.io/get_started/install.html#install-sglang).
 
 > [!Tip]
 > Due to the installing method of [`Flashinfer`](https://docs.flashinfer.ai/)-- a fast attention kernel library, we don't include the dependencies of `SGLang` within [pyproject.toml](pyproject.toml). Note that the `Flashinfer` also has some requirements on `torch` version.
 
-SGLang's server arguments are slightly different from other backends, see [here](https://docs.sglang.ai/backend/server_arguments.html) for more information. We provide an example of the usage here:
+SGLang's server arguments are slightly different from other backends, see [here](https://docs.sglang.io/advanced_features/server_arguments.html) for more information. We provide an example of the usage here:
 
 ```bash
 lm_eval --model sglang \