Update DeepSeek-V3_1.md for AMD GPU

DeepSeek/DeepSeek-V3_1.md

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         }
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+
+
+## AMD GPU Support
+Recommended approaches by hardware type are:
+
+MI300X/MI325X/MI355X 
+
+Please follow the steps here to install and run DeepSeek-V3.1 models on AMD MI300X/MI325X/MI355X GPU.
+
+### Step 1: Installing vLLM (AMD ROCm Backend: MI300X, MI325X, MI355X) 
+ > Note: The vLLM wheel for ROCm requires Python 3.12, ROCm 7.0, and glibc >= 2.35. If your environment does not meet these requirements, please use the Docker-based setup as described in the [documentation](https://docs.vllm.ai/en/latest/getting_started/installation/gpu/#pre-built-images).  
+ ```bash 
+ uv venv 
+ source .venv/bin/activate 
+ uv pip install vllm --extra-index-url https://wheels.vllm.ai/rocm/
+ ```
+
+
+### Step 2: Start the vLLM server
+
+Run the vllm online serving
+
+
+```bash
+SAFETENSORS_FAST_GPU=1 \
+VLLM_USE_TRITON_FLASH_ATTN=0 \
+VLLM_ROCM_USE_AITER=1 \
+vllm serve deepseek-ai/DeepSeek-V3.1 \
+  --tensor-parallel-size 8 \
+  --enable-expert-parallel \
+  --served-model-name ds31
+```
+
+
+### Step 3: Run Benchmark
+Open a new terminal and run the following command to execute the benchmark script.
+```bash
+vllm bench serve \
+  --model "deepseek-ai/DeepSeek-V3.1" \
+  --dataset-name random \
+  --random-input-len 8192 \
+  --random-output-len 1024 \
+  --request-rate 10000 \
+  --num-prompts 16 \
+  --ignore-eos \
+  --trust-remote-code
+```
+