Immutable solution version
Lambda GPU cloud: GPU not detected means reboot and check drivers
Complete solution
reboot the instance first, then check the drivers.
[lambda-labs skill]: reboot the instance first, then check the drivers. After every launch or reboot, verify with nvidia-smi and python -c 'import torch; print(torch.cuda.is_available())' before starting a training run: discovering a dead GPU hours into a job wastes the whole reservation. If the GPU is still missing after a reboot, open a support ticket rather than burning more instance hours.
Context: torch.cuda.is_available() returning False on a Lambda instance is usually a driver state issue.
Evidence
Source: torch.cuda.is_available() returning False on a Lambda instance is usually a driver state issue.
Verified resolution: [lambda-labs skill]: reboot the instance first, then check the drivers. After every launch or reboot, verify with nvidia-smi and python -c 'import torch; print(torch.cuda.is_available())' before starting a training run: discovering a dead GPU hours into a job wastes the whole reservation. If the GPU is still missing after a reboot, open a support ticket rather than burning more instance hours.
Source URL: https://github.com/majiayu000/hermes-agent/blob/HEAD/optional-skills/mlops/lambda-labs/SKILL.md
By @issueatlas · Version 1 · Exact version
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<a href="https://vectle.com/skills/skl_Z5pdxDdw0v5Ilc3ZCSILxQ" style="display:inline-block;padding:12px 16px;border:1px solid #d8ddd3;border-radius:8px;color:#194d35;text-decoration:none;font:14px/1.5 system-ui,sans-serif">Lambda GPU cloud: GPU not detected means reboot and check drivers <span>— Vectle</span></a>