su - rhcert -c 'ilab system info'

stdout:

ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no

ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no

ggml_cuda_init: found 4 CUDA devices:

Device 0: NVIDIA L40S, compute capability 8.9, VMM: yes

Device 1: NVIDIA L40S, compute capability 8.9, VMM: yes

Device 2: NVIDIA L40S, compute capability 8.9, VMM: yes

Device 3: NVIDIA L40S, compute capability 8.9, VMM: yes

Platform:

sys.version: 3.11.7 (main, Jan 8 2025, 00:00:00) [GCC 11.4.1 20231218 (Red Hat 11.4.1-3)]

sys.platform: linux

os.name: posix

platform.release: 5.14.0-427.65.1.el9_4.x86_64

platform.machine: x86_64

platform.node: localhost.localdomain

platform.python_version: 3.11.7

os-release.ID: rhel

os-release.VERSION_ID: 9.4

os-release.PRETTY_NAME: Red Hat Enterprise Linux 9.4 (Plow)

memory.total: 754.93 GB

memory.available: 747.56 GB

memory.used: 2.50 GB

InstructLab:

instructlab.version: 0.26.1

instructlab-dolomite.version: 0.2.0

instructlab-eval.version: 0.5.1

instructlab-quantize.version: 0.1.0

instructlab-schema.version: 0.4.2

instructlab-sdg.version: 0.8.2

instructlab-training.version: 0.10.2

Torch:

torch.version: 2.6.0

torch.backends.cpu.capability: AVX512

torch.version.cuda: 12.4

torch.version.hip: None

torch.cuda.available: True

torch.backends.cuda.is_built: True

torch.backends.mps.is_built: False

torch.backends.mps.is_available: False

torch.cuda.bf16: True

torch.cuda.current.device: 0

torch.cuda.0.name: NVIDIA L40S

torch.cuda.0.free: 43.9 GB

torch.cuda.0.total: 44.3 GB

torch.cuda.0.capability: 8.9 (see https://developer.nvidia.com/cuda-gpus#compute)

torch.cuda.1.name: NVIDIA L40S

torch.cuda.1.free: 43.9 GB

torch.cuda.1.total: 44.3 GB

torch.cuda.1.capability: 8.9 (see https://developer.nvidia.com/cuda-gpus#compute)

torch.cuda.2.name: NVIDIA L40S

torch.cuda.2.free: 43.9 GB

torch.cuda.2.total: 44.3 GB

torch.cuda.2.capability: 8.9 (see https://developer.nvidia.com/cuda-gpus#compute)

torch.cuda.3.name: NVIDIA L40S

torch.cuda.3.free: 43.9 GB

torch.cuda.3.total: 44.3 GB

torch.cuda.3.capability: 8.9 (see https://developer.nvidia.com/cuda-gpus#compute)

llama_cpp_python:

llama_cpp_python.version: 0.3.6

llama_cpp_python.supports_gpu_offload: True

stderr:

time="2025-09-23T10:34:03Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"

returned:

0

Running command - sudo -u rhcert -i -- bash -c ' ilab config init | tee /var/home/rhcert/ilab_init.log'

Review: Verify the ilab config init | tee /var/home/rhcert/ilab_init.log output