Lambda Labs Gpu Cloud
Skill ActiveReserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
To enable users to easily provision and manage dedicated GPU instances on Lambda Labs for ML training and inference, offering simple SSH access, persistent filesystems, and high-performance multi-node clusters.
Features
- Provisioning GPU instances (B200, H100, A100, etc.)
- SSH access and instance management
- Persistent filesystem integration
- High-performance multi-node cluster setup
- Comprehensive troubleshooting and usage guides
Use Cases
- Running long ML training jobs on dedicated GPUs
- Setting up persistent storage for datasets and models
- Deploying large-scale multi-GPU training clusters
- Leveraging pre-installed ML stacks (Lambda Stack)
Non-Goals
- Serverless or auto-scaling ML workloads (use Modal)
- Multi-cloud orchestration or cost optimization (use SkyPilot)
- Cheap spot instances or serverless endpoints (use RunPod)
- Lowest-price GPU marketplace (use Vast.ai)
Trust
- warning:Issues AttentionIn the last 90 days, 17 issues were opened and 4 were closed, indicating a low closure rate and potentially slow maintainer response.
Installation
npx skills add davila7/claude-code-templatesRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
Trust Signals
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