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Modal Serverless GPU

Run ML code on rented cloud GPUs in Python, with auto-scaling APIs and scheduled jobs.

Source Download skill
Repository
Orchestra-Research/AI-Research-SKILLs
Stars
14,195
Licence
MIT
Files
3 files

What it does

This skill teaches the agent how to use Modal, a cloud platform that runs your Python code on GPUs on demand, so you don't have to set up or manage servers. Once installed, the agent can write Modal code that picks a GPU type, packages dependencies into a container image, stores models in persistent volumes, deploys functions as web APIs, and schedules recurring jobs. You pay per second of GPU use and the platform scales down to zero when idle.

Great for

  • Developers who need occasional or bursty GPU compute for model inference, training or batch processing without managing infrastructure
  • Teams prototyping an ML model and wanting to expose it as an auto-scaling HTTP API quickly
  • People who want cron-style scheduled Python jobs that run on GPUs

Skip it if

  • Users who need a long-running pod with persistent state; the skill itself points to RunPod for that
  • Anyone handling sensitive data or credentials without reviewing the generated code, since the skill shows storing tokens in Modal secrets and the agent will run code against a paid cloud account
  • Users with no Python experience or no Modal account, since setup requires authenticating through a browser and a paid platform

Try asking

  • “Write a Modal function that runs a Whisper transcription on an A10G GPU and returns the text”
  • “Deploy my Hugging Face text-generation model as a POST web endpoint with auto-scaling”
  • “Set up a daily scheduled Modal job that processes yesterday's data on a T4 GPU”
  • “Show me how to cache model weights in a Modal Volume so they aren't re-downloaded each run”
Step-by-step guide: how to use Modal Serverless GPUInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 3 original files, the MIT licence and an attribution note.

    modal.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip modal.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip modal.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Start with modal run on a small GPU such as T4 to test before deploying an expensive A100 or H100 configuration
  • Review any generated code before running modal deploy, since deployments persist and bill continuously while active
  • Keep API tokens in Modal secrets rather than pasting them into code or prompts

What's inside

  • references/advanced-usage.md
  • references/troubleshooting.md
  • SKILL.md

Redistributed unmodified from Orchestra-Research/AI-Research-SKILLs under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.