alterlab-modal
De la autor
Runs Python code in the cloud with Modal — serverless containers, on-demand GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that need GPU acceleration or dynamic scaling. Part of the AlterLab Academic Skills suite.
Instalare
npx skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-modal -a claude-code
Se instalează în .claude/skills/alterlab-modal/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
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Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- modalK-Dense-AI/scientific-agent-skillsModal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.DevOps★ 54.5K
- alterlab-remote-computeAlterLab-IEU/AlterLab-Academic-SkillsDispatch long-running GPU/CPU jobs to remote compute with a provider-agnostic submit → poll → harvest pattern across SLURM/HPC (sbatch, squeue, sacct) and managed APIs (Modal, RunPod, GCP Batch / Vertex AI). Use when submitting a batch job to a cluster, polling job status, retrieving result artifacts from a scheduler or cloud GPU provider, or writing a portable job-submission wrapper; the foundation-model skills (alterlab-alphafold, alterlab-boltz, alterlab-rfdiffusion, and siblings) dispatch their GPU work through this pattern. For Modal-specific serverless container deployment and autoscaling prefer alterlab-modal instead. Part of the AlterLab Academic Skills suite.DevOps★ 78
- modal-serverless-gpuKalarisLabs/research-agent-skillsServerless 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.DevOps★ 61
- serverless-modalwanshuiyin/Auto-claude-code-research-in-sleepRun GPU workloads on Modal — training, fine-tuning, inference, batch processing. Zero-config serverless: no SSH, no Docker, auto scale-to-zero. Use when user says "modal run", "modal training", "modal inference", "deploy to modal", "need a GPU", "run on modal", "serverless GPU", or needs remote GPU compute.DevOps★ 18K
- runpodericrisco/rsc-harnessUse when running GPU compute on RunPod and deciding between Pods (hourly, always-on) and Serverless (per-second, autoscaling) for training, fine-tuning or inference — serverless endpoints, handler workers, worker Docker templates, network volumes, timeout and worker-count tuning, cold starts, and runaway bills. NOT Python-native serverless GPU with snapshot autoscaling (that is `modal`), NOT calling hosted prebuilt model APIs (that is `replicate`), NOT pulling weights from the Hub (that is `huggingface`).DevOps★ 272
- run-experimentwanshuiyin/Auto-claude-code-research-in-sleepDeploy and run ML experiments on local, remote, Vast.ai, or Modal serverless GPU. Use when user says "run experiment", "deploy to server", "跑实验", or needs to launch training jobs.DevOps★ 18K
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