[Docs] Re-arch on doc and make QwQ doc work (#271)

### What this PR does / why we need it?
Re-arch on tutorials, move singe npu / multi npu / multi node to index.
- Unifiy docker run cmd
- Use dropdown to hide build from source installation doc
- Re-arch tutorials to include Qwen/QwQ/DeepSeek
- Make QwQ doc works

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
CI test



Signed-off-by: Yikun Jiang <yikunkero@gmail.com>

docs/source/tutorials/multi_npu.md

@@ -0,0 +1,107 @@
+# Multi-NPU (QwQ 32B)
+
+## Run vllm-ascend on Multi-NPU
+
+Run docker container:
+
+```{code-block} bash
+   :substitutions:
+# Update the vllm-ascend image
+export IMAGE=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
+```
+
+Setup environment variables:
+
+```bash
+# Use Modelscope mirror to speed up model download
+export VLLM_USE_MODELSCOPE=True
+
+# To avoid NPU out of memory, set `max_split_size_mb` to any value lower than you need to allocate for Qwen2.5-7B-Instruct
+export PYTORCH_NPU_ALLOC_CONF=max_split_size_mb:256
+```
+
+### Online Inference on Multi-NPU
+
+Run the following script to start the vLLM server on Multi-NPU:
+
+```bash
+vllm serve Qwen/QwQ-32B --max-model-len 4096 --port 8000 -tp 4
+```
+
+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": "Qwen/QwQ-32B",
+        "prompt": "QwQ-32B是什么？",
+        "max_tokens": "128",
+        "top_p": "0.95",
+        "top_k": "40",
+        "temperature": "0.6"
+    }'
+```
+
+### Offline Inference on Multi-NPU
+
+Run the following script to execute offline inference on multi-NPU:
+
+```python
+import gc
+
+import torch
+
+from vllm import LLM, SamplingParams
+from vllm.distributed.parallel_state import (destroy_distributed_environment,
+                                             destroy_model_parallel)
+
+def clean_up():
+    destroy_model_parallel()
+    destroy_distributed_environment()
+    gc.collect()
+    torch.npu.empty_cache()
+
+prompts = [
+    "Hello, my name is",
+    "The future of AI is",
+]
+sampling_params = SamplingParams(temperature=0.6, top_p=0.95, top_k=40)
+llm = LLM(model="Qwen/QwQ-32B",
+          tensor_parallel_size=4,
+          distributed_executor_backend="tp",
+          max_model_len=4096)
+
+outputs = llm.generate(prompts, sampling_params)
+for output in outputs:
+    prompt = output.prompt
+    generated_text = output.outputs[0].text
+    print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
+
+del llm
+clean_up()
+```
+
+If you run this script successfully, you can see the info shown below:
+
+```bash
+Prompt: 'Hello, my name is', Generated text: ' Daniel and I am an 8th grade student at York Middle School. I'
+Prompt: 'The future of AI is', Generated text: ' following you. As the technology advances, a new report from the Institute for the'
+```