modal
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
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从固定版本的 SKILL.md 提取,保留原文语言。以下内容属于作者说明,本站尚未验证安装、兼容或运行结果。
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原文涵盖的主题
- Modal
- Overview
- When to Use This Skill
- Authentication and Setup
- Initial Setup
- Verify Setup
- Core Capabilities
- 1. Define Container Images
Modal is a serverless platform for running Python code in the cloud with minimal configuration. Execute functions on powerful GPUs, scale automatically to thousands of containers, and pay only for compute used. Modal is particularly suited for AI/ML workloads, high-performance batch processing, scheduled jobs, GPU inference, and serverless APIs. Sign up for free at https://modal.com and receive $30/month in credits. Use Modal for: Deploying and serving ML models (LLMs, image generation, embedding models) Running GPU-accelerated computation (training, inference, rendering) Batch processing large datasets in parallel Scheduling compute-intensive jobs (daily data processing, model training) Building serverless APIs that need automatic scaling Scientific computing requiring distributed compute or specialized hardware Modal requires authentication via API token. This creates a token stored in /.modal.toml. The token authenticates all Modal operations. Run with: modal run script.py Modal provides serverless Python execution through Functions that run in containers. Define compute requirements, dependencies, and scaling behavior declaratively. Specify dependencies and environment for func
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- 来源仓库
- davila7/claude-code-templates
- 源文件
- cli-tool/components/skills/scientific/modal/SKILL.md
- 固定版本
- 21be197f100a12b8d0dd9a211cc244c8179f84d3
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原作者:davila7/claude-code-templates · 原作者仓库元数据。文档核查:未核查。最近来源检查:2026-11-09T15:01:40.170Z。
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