modal

Topics in the source

• Modal
• Overview
• When to Use This Skill
• Authentication and Setup
• Initial Setup
• Verify Setup
• Core Capabilities
• 1. Define Container Images

Modal is a serverless platform for running Python code in the cloud with minimal configuration. Execute functions on powerful GPUs, scale automatically to thousands of containers, and pay only for compute used. Modal is particularly suited for AI/ML workloads, high-performance batch processing, scheduled jobs, GPU inference, and serverless APIs. Sign up for free at https://modal.com and receive $30/month in credits. Use Modal for: Deploying and serving ML models (LLMs, image generation, embedding models) Running GPU-accelerated computation (training, inference, rendering) Batch processing large datasets in parallel Scheduling compute-intensive jobs (daily data processing, model training) Building serverless APIs that need automatic scaling Scientific computing requiring distributed compute or specialized hardware Modal requires authentication via API token. This creates a token stored in /.modal.toml. The token authenticates all Modal operations. Run with: modal run script.py Modal provides serverless Python execution through Functions that run in containers. Define compute requirements, dependencies, and scaling behavior declaratively. Specify dependencies and environment for func

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