Reserved 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.
8.1
Rating
0
Installs
Machine Learning
Category
Excellent comprehensive skill for Lambda Labs GPU cloud management. The description clearly explains when to use Lambda Labs versus alternatives (Modal, RunPod, etc.), making it easy for a CLI agent to decide when to invoke this skill. Task knowledge is thorough with concrete Python API examples, curl commands, and multi-GPU training workflows including DDP/FSDP patterns. Structure is well-organized with clear sections, though SKILL.md is quite long; some subsections could potentially be moved to reference files for even better modularity. Novelty score is moderate because while GPU instance management is valuable, much of this involves straightforward API calls that a capable CLI agent could construct from API documentation. The skill shines in providing curated best practices (GPU selection, cost optimization, filesystem patterns) and ready-to-use training workflows that would require significant research to assemble from scratch. The inclusion of 1-Click Clusters and persistent filesystem patterns adds meaningful value beyond basic instance CRUD operations.
davila7
Skill Author
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