Menu

Individual skill

run-experiment

0upvotes

Deploy and run ML experiments on local, remote, Vast.ai, or Modal serverless GPU. Use when user says "run experiment", "deploy to server", "跑实验", or needs to launch training jobs.

skills/run-experiment/SKILL.md

Read pinned source

Source commit 2901234ad2954cd2388ced8d3aed2ed9de42803a

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
No
Observed behavior
Network or broad shell
Last checked
Nov 9, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
18,989
Repository last updated
Nov 8, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Run Experiment

Deploy and run ML experiment: $ARGUMENTS

## Workflow

### Step 1: Detect Environment

Read the project's `CLAUDE.md` to determine the experiment environment:

- **Local GPU** (`gpu: local`): Look for local CUDA/MPS setup info
- **Remote server** (`gpu: remote`): Look for SSH alias, conda env, code directory
- **Vast.ai** (`gpu: vast`): Check for `vast-instances.json` at project root — if a running instance exists, use it. Also check `CLAUDE.md` for a `## Vast.ai` section.
- **Modal** (`gpu: modal`): Serverless GPU via Modal. No SSH, no Docker, auto scale-to-zero. Delegate to `/serverless-modal`.
Back to top