[Doc] Add deepsee-v2-lite w8a8 quantization turorial (#630)

### What this PR does / why we need it?
Add deepsee-v2-lite w8a8 quantization turorial

---------

Signed-off-by: wangli <wangli858794774@gmail.com>

docs/source/tutorials/index.md

@@ -6,5 +6,6 @@
 single_npu
 single_npu_multimodal
 multi_npu
+multi_npu_quantization
 multi_node
 :::

docs/source/tutorials/multi_npu_quantization.md

@@ -0,0 +1,93 @@
+# Multi-NPU (deepseek-v2-lite-w8a8)
+
+## Run docker container:
+:::{note}
+w8a8 quantization feature is supported by v0.8.4rc2 or highter
+:::
+
+```{code-block} bash
+   :substitutions:
+# Update the vllm-ascend image
+export IMAGE=m.daocloud.io/quay.io/ascend/vllm-ascend:|vllm_ascend_version|
+docker run --rm \
+--name vllm-ascend \
+--device /dev/davinci0 \
+--device /dev/davinci1 \
+--device /dev/davinci2 \
+--device /dev/davinci3 \
+--device /dev/davinci_manager \
+--device /dev/devmm_svm \
+--device /dev/hisi_hdc \
+-v /usr/local/dcmi:/usr/local/dcmi \
+-v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
+-v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ \
+-v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
+-v /etc/ascend_install.info:/etc/ascend_install.info \
+-v /root/.cache:/root/.cache \
+-p 8000:8000 \
+-it $IMAGE bash
+```
+
+## Install modelslim and convert model
+:::{note}
+You can choose to convert the model yourself or use the quantized model we uploaded, 
+see https://www.modelscope.cn/models/vllm-ascend/DeepSeek-V2-Lite-w8a8
+:::
+
+```bash
+git clone https://gitee.com/ascend/msit
+
+# (Optional)This commit has been verified
+git checkout a396750f930e3bd2b8aa13730401dcbb4bc684ca
+cd msit/msmodelslim
+# Install by run this script
+bash install.sh
+pip install accelerate
+
+cd /msit/msmodelslim/example/DeepSeek
+# Original weight path, Replace with your local model path
+MODEL_PATH=/home/weight/DeepSeek-V2-Lite
+# Path to save converted weight, Replace with your local path
+SAVE_PATH=/home/weight/DeepSeek-V2-Lite-w8a8
+mkdir -p $SAVE_PATH
+# In this conversion process, the npu device is not must, you can also set --device_type cpu to have a conversion
+python3 quant_deepseek.py --model_path $MODEL_PATH --save_directory $SAVE_PATH --device_type npu --act_method 2 --w_bit 8 --a_bit 8  --is_dynamic True
+```
+
+## Verify the quantized model
+The converted model files looks like:
+```bash
+.
+|-- config.json
+|-- configuration_deepseek.py
+|-- fusion_result.json
+|-- generation_config.json
+|-- quant_model_description_w8a8_dynamic.json
+|-- quant_model_weight_w8a8_dynamic-00001-of-00004.safetensors
+|-- quant_model_weight_w8a8_dynamic-00002-of-00004.safetensors
+|-- quant_model_weight_w8a8_dynamic-00003-of-00004.safetensors
+|-- quant_model_weight_w8a8_dynamic-00004-of-00004.safetensors
+|-- quant_model_weight_w8a8_dynamic.safetensors.index.json
+|-- tokenization_deepseek_fast.py
+|-- tokenizer.json
+`-- tokenizer_config.json
+```
+
+Run the following script to start the vLLM server with quantize model:
+```bash
+vllm serve /home/weight/DeepSeek-V2-Lite-w8a8  --tensor-parallel-size 4 --trust-remote-code --served-model-name "dpsk-w8a8" --max-model-len 4096
+```
+
+Once your server is started, you can query the model with input prompts
+```bash
+curl http://localhost:8000/v1/completions \
+    -H "Content-Type: application/json" \
+    -d '{
+        "model": "dpsk-w8a8",
+        "prompt": "what is deepseek？",
+        "max_tokens": "128",
+        "top_p": "0.95",
+        "top_k": "40",
+        "temperature": "0.0"
+    }'
+```