modal
Cloud computing platform for running Python on GPUs and serverless infrastructure. Use when deploying AI/ML models, running GPU-accelerated workloads, serving web endpoints, scheduling batch jobs, or scaling Python code to the cloud. Use this skill whenever the user mentions Modal, serverless GPU compute, deploying ML models to the cloud, serving inference endpoints, running batch processing in the cloud, or needs to scale Python workloads beyond their local machine. Also use when the user wants to run code on H100s, A100s, or other cloud GPUs, or needs to create a web API for a model.
npx skills add BioTender-max/awesome-bio-agent-skills --skill modal --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Modal ## Overview Modal is a cloud platform for running Python code serverlessly, with a focus on AI/ML workloads. Key capabilities: - **GPU compute** on demand (T4, L4, A10, L40S, A100, H100, H200, B200) - **Serverless functions** with autoscaling from zero to thousands of containers - **Custom container images** built entirely in Python code - **Persistent storage** via Volumes for model weights and datasets - **Web endpoints** for serving models and APIs - **Scheduled jobs** via cron or fixed intervals - **Sub-second cold starts** for low-latency inference Everything in Modal is defined as code — no YAML, no Dockerfiles required (though both are supported). ## When to Use This Skill Use this skill when: - Deploy or serve AI/ML models in the cloud - Run GPU-accelerated computations (training, inference, fine-tuning) - Create serverless web APIs or endpoints - Scale batch processing jobs in parallel - Schedule recurring tasks (data pipelines, retraining, scraping) - Need persistent cloud storage for model weights or datasets - Want to run code in custom container environments - Build job queues or async task processing systems ## Installation and Authentication ### Install ```ba
- Overview
- When to Use This Skill
- Installation and Authentication
- Install
- Authenticate
- Core Concepts
- App and Functions
- Container Images
- GPU Compute
- Volumes (Persistent Storage)
- Secrets
- Web Endpoints
- Scheduled Jobs
- Scaling and Concurrency
uv pip install modal modal setup export MODAL_TOKEN_ID=<your-token-id> export MODAL_TOKEN_SECRET=<your-token-secret>
What does the modal skill do?
Cloud computing platform for running Python on GPUs and serverless infrastructure. Use when deploying AI/ML models, running GPU-accelerated workloads, serving web endpoints, scheduling batch jobs, or scaling Python code to the cloud. Use this skill whenever the user mentions Modal, serverless GPU compute, deploying ML models to the cloud, serving inference endpoints, running batch processing in the cloud, or needs to scale Python workloads beyond their local machine. Also use when the user wants to run code on H100s, A100s, or other cloud GPUs, or needs to create a web API for a model.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill modal --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.