Agent Skills › advaitpaliwal/feynman › modal-compute

modal-compute

GitHub

用于在Modal无服务器基础设施上运行研究基准测试或模型复现任务，提供突发GPU算力支持。适用于无需持久状态、需快速执行且依赖Modal CLI的研究实验场景。

skills/modal-compute/SKILL.md advaitpaliwal/feynman

Trigger Scenarios

需要运行GPU密集型研究实验进行模型复现或基准测试需要突发GPU算力但无持久状态需求

Install

npx skills add advaitpaliwal/feynman --skill modal-compute -g -y

More Options

Use without installing

npx skills use advaitpaliwal/feynman@modal-compute

指定 Agent (Claude Code)

npx skills add advaitpaliwal/feynman --skill modal-compute -a claude-code -g -y

安装 repo 全部 skill

npx skills add advaitpaliwal/feynman --all -g -y

预览 repo 内 skill

npx skills add advaitpaliwal/feynman --list

SKILL.md

Frontmatter

{
    "name": "modal-compute",
    "description": "Run explicitly chosen research benchmark or replication jobs on Modal's serverless infrastructure. Use when a Feynman research workflow needs burst remote GPU compute and the Modal CLI is available."
}

Modal Compute

Use the modal CLI for bounded research experiments that need burst GPU compute. No pod lifecycle to manage; write a decorated Python script, run it, and save raw outputs back into the research artifact folder. Do not use this skill to deploy services or unrelated batch jobs.

Setup

pip install modal
modal setup

Commands

Command	Description
`modal run script.py`	Run one research experiment script on Modal
`modal run --detach script.py`	Run a long research experiment and record the returned app/run identifier
`modal shell --gpu a100`	Open an interactive GPU shell for research environment debugging

GPU types

T4, L4, A10G, L40S, A100, A100-80GB, H100, H200, B200

Multi-GPU: "H100:4" for 4x H100s.

Script pattern

import modal

app = modal.App("experiment")
image = modal.Image.debian_slim(python_version="3.11").pip_install("torch==2.8.0")

@app.function(gpu="A100", image=image, timeout=600)
def train():
    import torch
    # training code here

@app.local_entrypoint()
def main():
    train.remote()