Modal Serverless Gpu
技能 活跃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.
To enable users to run GPU-intensive ML workloads on-demand without managing infrastructure, by leveraging Modal's serverless platform for deployment and batch processing.
功能
- Serverless GPU access (T4, L4, A10G, A100, H100, etc.)
- On-demand ML model deployment as APIs
- Automatic scaling for batch jobs and inference
- Python-native infrastructure definition
- Sub-second cold starts and container caching
使用场景
- Running GPU-intensive ML workloads without managing infrastructure
- Deploying ML models as auto-scaling APIs
- Running batch processing jobs (training, inference, data processing)
- Prototyping ML applications quickly
非目标
- Providing reserved GPU instances
- Orchestrating multi-cloud deployments
- Managing complex multi-service architectures directly
Trust
- warning:Issues AttentionIn the last 90 days, 17 issues were opened and 4 were closed, indicating a closure rate below 50% and a significant number of open issues, suggesting potential delays in maintainer response.
安装
npx skills add davila7/claude-code-templates通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
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