Update the mixtral to use the better FusedMoE layer (#1081)

docs/en/model_support.md

@@ -5,7 +5,7 @@ To support a new model in SGLang, you only need to add a single file under [SGLa
 Another valuable resource is the [vLLM Models Directory](https://github.com/vllm-project/vllm/tree/main/vllm/model_executor/models). vLLM has extensive coverage of models, and SGLang has reused vLLM for most parts of the model implementations. This similarity makes it easy to port many models from vLLM to SGLang.
 
 To port a model from vLLM to SGLang, you can compare these two files [SGLang LLaMA Implementation](https://github.com/sgl-project/sglang/blob/main/python/sglang/srt/models/llama2.py) and [vLLM LLaMA Implementation](https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/models/llama.py). This comparison will help you understand how to convert a model implementation from vLLM to SGLang. The major difference is the replacement of PagedAttention with RadixAttention. The other parts are almost identical. Specifically,
-  - Replace vllm's `Attention` with `RadixAttention`.
+  - Replace vllm's `Attention` with `RadixAttention`. Note that you need to pass `layer_id` all the way to `RadixAttention`.
   - Replace vllm's `LogitsProcessor` with SGLang's `LogitsProcessor`.
   - Remove `Sample`.
   - Change `forward()` functions, and add `input_metadata`.