Can I use this for building web APIs?

Absolutely. The skill includes patterns for deploying web endpoints and FastAPI integrations that scale automatically from zero based on incoming traffic.

How do I authenticate Modal within Claude Code?

The skill provides instructions for installing the Modal client via 'uv' and running 'modal token new' to authenticate your local environment with an API token.

Does this skill support GPU acceleration?

Yes, the skill provides patterns and guidance for requesting various GPU types including H100s, A100s, and L40S for high-performance training and inference.

What is the Modal skill for Claude Code?

It is a specialized capability that allows Claude to help you write, deploy, and manage serverless Python applications on the Modal platform, including GPU-accelerated ML workloads.

How does Modal handle persistent data?

The skill demonstrates how to use Modal Volumes to store and persist data, model weights, and caches across different function invocations and deployments.

Modal Serverless Python

Name: Modal Serverless Python
Author: pur3v4d3r

bypur3v4d3r

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Cloud Infrastructure

Deploys and scales Python functions, ML models, and GPU-intensive tasks on serverless cloud infrastructure with minimal configuration.

About

Modal is a specialized skill for Claude Code that empowers developers to run Python code in the cloud without managing complex infrastructure. It provides seamless integration for deploying machine learning models, running massive batch processing jobs, and executing GPU-accelerated workloads. By leveraging Modal's autoscaling containers and persistent storage, this skill enables Claude to help you build, deploy, and scale data-intensive applications, serverless APIs, and scheduled background tasks directly from your development environment, allowing you to focus on code rather than devops.

Key Features

Deployment of web endpoints, FastAPI integrations, and scheduled cron jobs
Declarative container image building with Python and system dependencies
Automatic horizontal scaling from zero to thousands of concurrent containers
Serverless GPU computing for ML training and inference (H100, A100, L40S)
Persistent storage via Modal Volumes and secure secret management
1 GitHub stars

Use Cases

Deploying LLMs or image generation models with high-performance GPU acceleration
Parallelizing large-scale data processing or scientific simulation tasks
Building autoscaling serverless APIs and automated scheduled data pipeline jobs

About

Key Features

Deployment of web endpoints, FastAPI integrations, and scheduled cron jobs
Declarative container image building with Python and system dependencies
Automatic horizontal scaling from zero to thousands of concurrent containers
Serverless GPU computing for ML training and inference (H100, A100, L40S)
Persistent storage via Modal Volumes and secure secret management
1 GitHub stars

Use Cases

Deploying LLMs or image generation models with high-performance GPU acceleration
Parallelizing large-scale data processing or scientific simulation tasks
Building autoscaling serverless APIs and automated scheduled data pipeline jobs