1. Recommended Configuration for Running Stable Diffusion Memory: at least 16 GB DDR4 or DDR5 Storage: at least 10 GB of free space GPU: an NVIDIA card with at least 6 GB of VRAM If your hardware falls short, you can also use one of the various optimized forks that support lower-spec hardware, but generation time will increase.

I wrote about this in an earlier post, How to Install a GPU Driver on CentOS. This one looks at how to run TensorFlow with Docker. 1. Check Which TensorFlow Version the Current CPU Supports On a CPU that does not support AVX instructions, running TensorFlow > 1.15 fails with Illegal instruction (core dumped).

Using CentOS 7.7 and a Tesla P100 GPU as an example. 1. Preparing the Base Environment Install the lspci command 1 yum install -y pciutils Check whether the GPU supports CUDA 1 2 3 lspci | grep -i nvidia 00:09.0 3D controller: NVIDIA Corporation GP100GL [Tesla P100 PCIe 12GB] (rev a1) List of CUDA-capable GPUs: https://developer.