runpod
De la autor
Use 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`).
Instalare
npx skills add ericrisco/rsc-harness --skill runpod -a claude-code
Se instalează în .claude/skills/runpod/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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De ce 79
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
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
- 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
- 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
- alterlab-modalAlterLab-IEU/AlterLab-Academic-SkillsRuns 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.DevOps★ 78
- 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
- rented-server-setupnaveedharri/benai-skillsRuns an open model in the cloud two ways, and makes the user choose with real numbers. Route A is OVHcloud AI Endpoints, an EU-owned per-token API with zero idle cost, for spiky usage and EU jurisdiction. Route B rents one single-tenant RunPod GPU pod in a region the user picks, serving the model on vLLM behind a generated API key, with Open WebUI behind its own login and a URL Claude Code can use directly, for sustained use, unlisted models, or single tenancy. Use when the user says "rent a GPU", "run a big model in the cloud", "my machine cannot run this model", "deploy an open model", "host Qwen or DeepSeek or GLM myself", "put Open WebUI online", "give my team a private ChatGPT", "private AI for my business", "GDPR compliant LLM hosting", "data must stay in the EU", "EU AI API", "pay per token", "OVHcloud", "AI Endpoints", "RunPod", or "cloud GPU". Asks which build fits, never picks a region, and always shows cost before spending. Requires shell and internet access; refuses to run in a sandbox.DevOps★ 74
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