modal-serverless-gpu

What problem does it solve?

This Skill provides a serverless GPU cloud platform for running machine learning workloads, simplifying the deployment of ML models as APIs and the execution of batch jobs with automatic scaling.

Core Features & Use Cases

• Serverless GPU Access: On-demand access to various GPU types (T4, L4, A10G, A100, H100, etc.) without infrastructure management.
• ML Model Deployment: Deploy ML models as auto-scaling REST APIs.
• Batch Processing: Run training, inference, or data processing jobs with automatic scaling.
• Use Case: You need to deploy a large language model for real-time inference. Instead of managing your own GPU servers, you can use Modal to deploy it as a scalable API endpoint that automatically handles traffic spikes.

Quick Start

Use the modal-serverless-gpu skill to deploy a Python function that uses an A10G GPU.