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serverless-modal

Enables GPU workloads on Modal from local code without SSH or Docker setup.

Updated Apr 21, 2026
Search Tags:#deployment#serverless#modal#inference#cost estimation#vllm#gpu training
One-click install
npx skills add https://github.com/Shallow-W/llm-wiki --skill serverless-modal-shallow-w
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: serverless-modal
Source: https://github.com/Shallow-W/llm-wiki/tree/main/.claude/skills/serverless-modal
Command: npx skills add https://github.com/Shallow-W/llm-wiki --skill serverless-modal-shallow-w

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It eliminates the friction of setting up remote GPU machines by letting you run GPU workloads from your local environment using Modal’s serverless infrastructure.

Core Features & Use Cases

  • Zero-config GPU runs: avoids SSH, Docker, and port-forwarding while running code remotely.
  • Auto scale-to-zero: bills only while the workload executes, helping control costs for short experiments and benchmarks.
  • Practical GPU workload patterns: supports one-shot training/evaluation runs, persistent inference services, vLLM-based serving, batch processing, LoRA fine-tuning, and multi-GPU distributed training.

Quick Start

Ask the skill to run your GPU task on Modal by providing your desired command or training/inference description, for example: Run training for my model on Modal and include a cost estimate and GPU selection based on expected VRAM.

Frequently Asked Questions about serverless-modal

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run GPU training and inference without setting up Docker or SSH?▼

You can execute serverless GPU workloads directly from local code using Modal to eliminate SSH and Docker setup. This approach handles training, fine-tuning, and inference while automatically scaling to zero to control costs.

Can I deploy a vLLM server for inference on Modal?▼

Yes, you can deploy a vLLM server on Modal for serverless inference. The skill generates an appropriate Modal launcher configuration matched to your requested serving pattern, avoiding manual remote deployment.

Does GPU training on Modal provide cost estimation before running?▼

Yes, serverless GPU runs on Modal require per-run cost estimation with user confirmation before execution. This ensures you understand expected costs based on your GPU selection and workload duration.

What is the best way to perform LoRA fine-tuning and multi-GPU training remotely?▼

The best way is using serverless deployment patterns on Modal, which support LoRA tuning and multi-GPU distributed training. This bypasses manual infrastructure management and bills only during execution.

How do I deploy a FastAPI service for GPU batch processing without manual port-forwarding?▼

You can deploy FastAPI services for GPU batch processing on Modal without port-forwarding. The serverless infrastructure auto-scales to handle requests and scales to zero when idle to minimize expenses.

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