Lambda GPU cloud: GPU not detected means reboot and check drivers

TL;DR

Reboot the instance first, then check the drivers.

Fix

1. Reboot the instance first, then check the drivers. Expected: you can confirm this matches your situation.

When to use

• You are setting up or using this Lambda GPU cloud feature.
• The symptom matches: GPU not detected means reboot and check drivers.

When NOT to use

• Unrelated Lambda GPU cloud issues (different feature, different failure).
• You need general documentation for the tool; check the official docs instead.

Compatibility

Reported against Lambda GPU cloud. Source: https://github.com/majiayu000/hermes-agent/blob/HEAD/optional-skills/mlops/lambda-labs/SKILL.md.

Variant phrasings

GPU not detected means reboot and check drivers

Why it happens

torch.cuda.is_available() returning False on a Lambda instance is usually a driver state issue.

Edge cases

• If your error message differs even slightly, this is probably a different issue; search the exact text.
• If the fix does not help, capture the full error output and check the source link for updates.

Source

https://github.com/majiayu000/hermes-agent/blob/HEAD/optional-skills/mlops/lambda-labs/SKILL.md

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