Scaffold, configure, and launch ML experiments with SLURM submission scripts.
npx skills add https://github.com/michaelrizvi/claude-config --skill experiment
Please help me install this Agent Skill. Skill: experiment Source: https://github.com/michaelrizvi/claude-config/tree/main/skills/experiment Command: npx skills add https://github.com/michaelrizvi/claude-config --skill experiment
Reduce setup time and errors by scaffolding, configuring, and launching ML experiments.
Ask this Skill to scaffold a new experiment with a minimal config and a SLURM submission script.
High-intent search queries and answers about installing and using this skill.
Scaffold ML experiments by generating standardized configurations, scripts, and run tracking structures to ensure reproducible training. This approach reduces setup time and errors by providing a minimal project configuration with logging hooks for consistent experiment organization.
Yes, you can launch hyperparameter sweeps and evaluations on SLURM-managed clusters. The process provides SLURM submission guidance to ensure reproducible runs across both local machines and managed cluster environments.
The best way to reduce setup errors is scaffolding experiments with standardized configs, scripts, and run tracking. This ensures consistent organization and reproducibility by enforcing minimal project configurations and logging hooks from the start.
Yes, a minimal project configuration is required to start planning training runs. This setup includes logging hooks and standardized scripts to guarantee reproducible runs when executing evaluations locally or on SLURM clusters.
Scaffolding improves reproducibility by enforcing standardized configs and logging hooks across all environments. This ensures that training runs, hyperparameter sweeps, and evaluations execute consistently whether launched on local machines or SLURM-managed clusters.
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dongzhuoyaoSubmit GPU training jobs to Slurm clusters with preflight validation and monitoring.
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