modal-serverless-gpu Skill
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling. Published by NousResearch in hermes-agent.
What is modal-serverless-gpu Skill?
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling. Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Deployment
- Data analysis
- Design and media
- Deployment use cases
- Data analysis use cases
Technical details
- Install or run with Copy skill directory
When to use modal-serverless-gpu Skill
- Use it for deployment.
- Use it for data analysis.
- Use it for design and media.
Built with
Editorial notes
Source
- Creator: NousResearch
- Repository: NousResearch/hermes-agent
- Skill file: optional-skills/mlops/modal/SKILL.md
What it does
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
Skill instructions
Modal Serverless GPU Comprehensive guide to running ML workloads on Modal's serverless GPU cloud platform. When to use Modal Use Modal when: - Running GPU-intensive ML workloads without managing infrastructure - Deploying ML models as auto-scaling APIs - Running batch processing jobs (training, inference, data processing) - Need pay-per-second GPU pricing without idle costs - Prototyping ML applications quickly - Running scheduled jobs (cron-like workloads) Key features: - Serverless GPUs: T4, L4, A10G, L40S, A100, H100, H200, B200 on-demand - Python-native: Define infrastructure in Python code, no YAML - Auto-scaling: Scale to zero, scale to 100+ GPUs instantly - Sub-second cold starts: Rust-based infrastructure for fast container launches - Container caching: Image layers cached for rapid iteration - Web endpoints: Deploy functions as REST APIs with zero-downtime updates Use alternatives instead: - RunPod: For longer-running pods with persistent state - Lambda Labs: For reserved GPU
Explore related resources
Frequently asked questions
What is modal-serverless-gpu?
modal-serverless-gpu is a open-source AI agent skill with Copy skill directory. Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic.
Who is modal-serverless-gpu best for?
modal-serverless-gpu is best for reusing agent instructions, scripts, and references, deployment workflows, data analysis workflows, design and media workflows.
How do I install modal-serverless-gpu?
Install or run modal-serverless-gpu using Copy skill directory. Check modal-serverless-gpu for the latest setup command.
Is modal-serverless-gpu actively maintained?
modal-serverless-gpu may need a closer maintenance check before production use.
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