CUDA Error : CUDA driver version is insufficient for CUDA runtime version

^{Originally posted by **VijayAsokkumar** May 3, 2024}
Hi All,
I am using llamacpppython in my app, which I have installed in a conda environment. I have built a chat application using the LLaMA 2 7b model with Python Flask. I was able to use it on my laptop with an M1 chip. However, when I try to deploy the app on an AWS g4dn.xlarge instance with a Tesla T4 GPU, I am facing the following error whenever the app tries to use llamacpppython:

CUDA error 35 at /home/conda/feedstock_root/build_artifacts/llama.cpp_1703017359354/work/ggml-cuda.cu:493: CUDA driver version is insufficient for CUDA runtime version
GGML_ASSERT: /home/conda/feedstock_root/build_artifacts/llama.cpp_1703017359354/work/ggml-cuda.cu:493: !"CUDA error"

$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2023 NVIDIA Corporation
Built on Wed_Nov_22_10:17:15_PST_2023
Cuda compilation tools, release 12.3, V12.3.107
Build cuda_12.3.r12.3/compiler.33567101_0

Essentially, I need suggestions on the following areas:

The supported CUDA driver version for the Tesla T4 GPU, as the AWS instance runs on Ubuntu 18.04.
I noticed that the default CUDA driver is version 9, and I have installed version 12.3. I need guidance on how to configure the latest CUDA driver within the conda environment.
Instructions on how to enable the app to utilize the GPU.

Thanks,
Vijay Asokkumar