Which GPUs can I request using this skill?

You can request a wide range of NVIDIA GPUs including the T4, L4, A10, A100, L40S, H100, H200, and the high-performance B200.

How does Modal handle persistent data?

Modal uses Volumes to provide persistent storage across function invocations, which is perfect for storing model weights, caching datasets, or sharing data between distributed tasks.

What is the Modal Claude Code Skill?

It is a specialized capability that allows Claude to write, configure, and deploy serverless Python code onto the Modal platform, providing easy access to cloud compute and specialized hardware.

Can I use this skill to build web APIs?

Yes, Modal supports web endpoints and FastAPI integration, allowing you to deploy serverless APIs, webhooks, and streaming services with a single decorator.

Is there a cost associated with using Modal?

Modal follows a pay-per-compute model. However, they typically offer a free tier with monthly credits for new users to explore the platform.

Modal Cloud Infrastructure

Name: Modal Cloud Infrastructure
Author: K-Dense-AI

byK-Dense-AI

•

3,718

클라우드 인프라

Executes Python code in the cloud with serverless containers, on-demand GPU acceleration, and automatic scaling for AI and scientific workloads.

소개

Modal provides a seamless serverless platform for deploying Python-based AI models and scientific workloads without the burden of manual infrastructure management. This skill enables Claude to configure container images, request high-performance GPUs like H100s or B200s, and scale compute tasks from zero to thousands of containers automatically. It is ideal for developers needing to run parallel batch processing, serve real-time ML APIs, or perform complex simulations while benefiting from integrated secret management and persistent storage volumes.

주요 기능

Serverless Python execution with automatic scaling to thousands of containers
3,718 GitHub stars
Declarative container image building with optimized package installation
Persistent data storage through Modal Volumes for large datasets and weights
Integrated secret management and instant web endpoint deployment
On-demand access to high-performance GPUs including H100 and B200

사용 사례

Running massively parallel batch processing jobs on large-scale scientific datasets
Scheduling recurring compute-intensive tasks like daily model retraining or data pipelines
Deploying and serving LLMs or image generation models with GPU acceleration

소개

주요 기능

Serverless Python execution with automatic scaling to thousands of containers
3,718 GitHub stars
Declarative container image building with optimized package installation
Persistent data storage through Modal Volumes for large datasets and weights
Integrated secret management and instant web endpoint deployment
On-demand access to high-performance GPUs including H100 and B200

사용 사례

Running massively parallel batch processing jobs on large-scale scientific datasets
Scheduling recurring compute-intensive tasks like daily model retraining or data pipelines
Deploying and serving LLMs or image generation models with GPU acceleration