What problem does it solve?
Running GPU workloads like model training, fine-tuning, and inference typically requires SSH access, Docker setup, and manual instance management. This Skill lets you execute those workloads on Modal's serverless GPU cloud directly from your local machine, with automatic scale-to-zero billing.
Core Features & Use Cases
- Serverless GPU Execution: Generate and run Modal launcher scripts for training, evaluation, and benchmarking without SSH or Docker configuration.
- Cost Estimation & GPU Selection: Analyze model size and VRAM requirements to pick the right GPU (T4 through B200) and estimate cost before every run.
- Multiple Workload Patterns: Supports one-shot training functions, persistent FastAPI inference services, vLLM serving, batch parallel processing, LoRA fine-tuning, and multi-GPU distributed training.
- Use Case: You need to fine-tune a 7B model but have no local GPU. The Skill generates a Modal launcher with an A100-80GB, mounts your local code, persists checkpoints to a Modal volume, and runs it with a single
modal run command.
Quick Start
Ask the assistant to run your training script on Modal with an A100 GPU and confirm the cost estimate before execution.
