Install guide and quick start are misleading and not aligned

[EmilioZhao]

System Info

• GPU ：rtx 3080

• I've just follow "installation" guide from quick start step by step https://github.com/NVIDIA/TensorRT-LLM/blob/main/docs/source/installation/linux.md

• All the operations were done in the docker which is suggested optional in the guide.

  # Obtain and start the basic docker image environment (optional).
  docker run --rm --ipc=host --runtime=nvidia --gpus all --entrypoint /bin/bash -it nvidia/cuda:12.4.1-devel-ubuntu22.04

  I've finished Check installation python3 -c "import tensorrt_llm" returned correct tensorrt_llm version:

• however, when I finished all the steps in installation and start the section "Compile the Model into a TensorRT Engine"

• I can not run "make -C docker release_run LOCAL_USER=1" in the docker, because I was in the docker of nvidia/cuda:12.4.1-devel-ubuntu22.04 already.

• So I just directly run the following steps to convert llama weights and build.

• Converting weights was successful but trtllm_build failed because torch can't find CUDA Device.

• I've checked cuda driver running status by nvidia-smi, and it returned a normal result with 535.183.06.

• I found that there're two different versions of CUDA version were installed. Maybe one was already installed in the docker, while the other was installed by pip dependency of tensorrt_llm.

• I don't know whether is the problem of docker nvidia/cuda:12.4.1-devel-ubuntu22.04 or I shoud build another docker on the host by make -C docker release_run LOCAL_USER=1

• Quick start is really import for someone new to tensorrt-llm, It took me several hours to run through this guide, It's irresponsible not to double check all the steps related while upgrade the repository.

Who can help?

The one who wrote quick start.

Information

• [x] The official example scripts
• [ ] My own modified scripts

Tasks

• [x] An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
• [ ] My own task or dataset (give details below)

Reproduction

1. mentioned above: running all the installation in the docker of nvidia/cuda:12.4.1-devel-ubuntu22.04

Expected behavior

1. build succ.

actual behavior

1. Two versions of libcuda.so were found and trtllm_build failed.

additional notes

nope

[EmilioZhao]

I tried make -C docker build and successfully built docker, but can not run LLama demo because of the incompatibility of CUDA driver and CUDA 12.5! Commented in the issue: https://github.com/NVIDIA/TensorRT-LLM/issues/601#issuecomment-2339467644 But nobody replies!