Launch and manage ML experiments across local, remote, Vast.ai, and Modal environments.
npx skills add https://github.com/jkfee/Auto-Research --skill run-experiment-jkfee
Please help me install this Agent Skill. Skill: run-experiment Source: https://github.com/jkfee/Auto-Research/tree/main/skills/run-experiment Command: npx skills add https://github.com/jkfee/Auto-Research --skill run-experiment-jkfee
Deploy and manage end-to-end ML experiments across local GPUs, remote servers, Vast.ai, or Modal with automatic setup, monitoring, and teardown.
Ask the skill to deploy and run your ML experiment across your chosen compute backends.
High-intent search queries and answers about installing and using this skill.
To run ML experiments across local and cloud GPUs, this skill automates environment detection, pre-flight checks, code synchronization, deployment, monitoring, and teardown across diverse compute backends.
Yes, this skill supports deploying machine-learning models to Vast.ai and Modal. It provides multi-backend support for local workstations, remote SSH servers, Vast.ai rentals, and serverless Modal environments.
The best way to manage ML experiment lifecycle and cleanup on remote servers is using an automation tool that handles pre-flight checks, code synchronization, deployment, and cost-aware teardown to ensure repeatable runs.
Yes, you can use Weights and Biases integration when running machine-learning experiments on remote GPUs. The skill implements optional W&B integration during the deployment and monitoring phases.
To synchronize code and run pre-flight checks before launching a GPU experiment, the skill automatically detects the target environment, validates prerequisites, and syncs your codebase before deployment.
Yes, there are cost-aware features for auto-destroying Vast.ai instances after an experiment finishes. The skill includes post-run cleanup with cost-aware handling and auto-destroy for Vast.ai rentals.
Mang30Launches ML training jobs on local, SSH, Vast.ai, or Modal GPUs with logging.
TheCraigHewittPlan A/B tests with hypotheses, sample sizes, and metrics documentation.
RheasilviaLog machine learning experiment metrics and hyperparameters to Weights & Biases.
FutureAtomsAutomate PersonaPlex deployment to cloud GPU infrastructure with auto-scaling and cost optimization.
