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.
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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.
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Transcribes local audio and video to txt, srt, vtt and json with timestamps using whisper.cpp, and proves which backend ran. Trigger to transcribe, caption or subtitle a recording, meeting, podcast or video locally; to pick a Whisper model for this GPU or estimate a batch; when a transcript is empty, cut short or repeating; when Whisper ran on the CPU or a pasted log must prove the GPU ran; when it shares the GPU with LM Studio or ComfyUI; or say whisperrunner (audit, check, plan, run, status, refresh). Never a cloud API or a download. Voice-overs are comfyrunner's; clips and burned-in captions obsrunner's; game audio soundsmith's; summarising transcripts lmstudiorunner's.
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Run molecular property predictions, explore molecular shapes, and estimate how compounds bind to proteins through a cloud Python API. Process compound batches and connect modeling steps without maintaining local high-performance computing infrastructure.
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Create a custom voice from an authorized speech sample, then synthesize scripts for narration, spoken presentations, or product promotion. Cloud providers generate mp3 or wav audio using supplied credentials, without requiring a local GPU.
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dstack is an open-source control plane for GPU provisioning and orchestration across GPU clouds, Kubernetes, and on-prem clusters.
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Cloudflare Workers AI for serverless GPU inference. Use for LLMs, text/image generation, embeddings, or encountering AI_ERROR, rate limits, token exceeded errors.
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Optimizing FinOps and cloud cost: IaC-based estimation, right-sizing, RI/SP recommendations, anomaly detection, budget alerts, AI/GPU workload economics. Use to forecast or cut cloud spend.
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Build interactive live slide decks with Vite + React 19, TanStack Router, WebGPU shaders, Framer Motion orchestration, 1920x1080, access-gated SPA. 39 components (layout, interaction, graphics, chrome, navigation), direction-aware slide transitions, presenter mode with speaker notes and BroadcastChannel sync, Playwright PNG/PDF export, YAML-driven authoring, Cloudflare/Vercel/Netlify deploy. Triggers on: slide deck, presentation, pitch deck, investor deck, product demo, conference talk, live slides, WebGPU slides, interactive presentation, presenter mode, speaker notes, overwatch deck.
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Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, LoRA training for character consistency, motion graphics generation, and artist commissioning. Activate on 'AI video production', 'script to video', 'video generation pipeline', 'character consistency', 'LoRA training', 'cloud GPU', 'motion graphics', 'Wan I2V', 'InVideo alternative'. NOT for real-time video editing, video compositing (use DaVinci/Premiere), audio production, or 3D modeling (use Blender/Maya).
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Use when working with Azure Container Instances — azure Container Instances management covering container group inventory, container status and restart counts, CPU and memory utilization, networking configuration, log retrieval, and GPU allocation tracking. Use for ACI workload monitoring and troubleshooting.
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Use when working with Baseten — baseten ML deployment platform management covering model inventory, deployment status, autoscaling configuration, inference call history, GPU allocation, environment management, and performance metrics. Use for comprehensive Baseten workspace assessment and ML serving optimization.
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Use when working with Banana Dev — banana.dev ML inference platform management covering model inventory, deployment status, API call history, GPU allocation, scaling configuration, build logs, and latency metrics. Use for comprehensive Banana.dev model deployment assessment and inference performance analysis.
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Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
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Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, LoRA training for character consistency, motion graphics generation, and artist commissioning. Activate on 'AI video production', 'script to video', 'video generation pipeline', 'character consistency', 'LoRA training', 'cloud GPU', 'motion graphics', 'Wan I2V', 'InVideo alternative'. NOT for real-time video editing, video compositing (use DaVinci/Premiere), audio production, or 3D modeling (use Blender/Maya).
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Explains how to run NemoClaw on a remote GPU instance, including the deprecated Brev compatibility path and the preferred installer plus onboard flow. Use when deploying NemoClaw to a remote VM, onboarding a Brev instance, or migrating away from the legacy `nemoclaw deploy` wrapper. Trigger keywords - deploy nemoclaw remote gpu, nemoclaw brev cloud deployment, nemoclaw sandbox hardening, container security, docker capabilities, process limits, nemoclaw telegram, telegram bot openclaw agent, openshell channel messaging.
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공통 명령으로 150개 이상의 클라우드 AI 앱을 찾아 실행합니다. 이미지와 영상 생성, AI 검색을 지원하며 로컬 이미지와 음성으로 가공하거나 아바타 영상을 만듭니다.
Choose tools and workflows for 3D modeling, dimensioned CAD parts, scan processing, rendering, and fabrication. Capability tables and recipes help connect tasks from photographs or initial designs to printable parts, CNC toolpaths, or game assets.
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Turn dialogue scripts into an audio track with a distinct voice for each character and timed subtitles naming each speaker. Supported cloud speech services can also use emotion labels to shape how individual lines are delivered.
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Deploy, run, and test NVIDIA speech recognition, speech synthesis, and translation services in the cloud or on your own infrastructure. Guidance covers model selection, environment checks, custom models, and adjustments to speech processing and pronunciation.
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AWS Startups reference content — Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies. Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic. For copy-paste AI prompts (RAG chatbot, MVP scaffold, security baseline, GPU quota, etc.), see the prompt-library-for-startups skill. Do not use for: account-specific lookups (credits balance, Activate membership status, application status), real-time event listings beyond the events stub, or content not present in the bundled `references/` tree.
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Use when the user asks to run heavy or GPU work on Modal (the cloud compute platform) — writing a Modal function in the workspace, running it with the user's own `modal` CLI + token, and bringing results back. Data-to-compute for jobs too big for the laptop, without a Slurm cluster.
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Add p-value brackets, significance asterisks, and effect-size annotations to distribution plots using ggpubr, ggsignif, and statannotations with correct test selection (parametric vs non-parametric vs paired), multiple-testing adjustment, and rendering of negative results. Use when a boxplot/violin/raincloud needs in-figure statistical comparisons between groups.
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This skill should be used when user asks to "upload my model to Ultralytics Platform", "push this run to the platform", "upload a dataset to platform", "download a dataset from platform", "search platform datasets", "start cloud training", "train on platform GPUs", "export a model on platform", "deploy a model endpoint", "run Moondream on Platform", "auto-annotate a Platform dataset", "run hosted AI inference", "why is my run not showing on platform", or mentions platform.ultralytics.com, ul:// URIs, ultralytics-platform, or ULTRALYTICS_API_KEY.
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Fast in-memory DataFrame with lazy evaluation, parallel execution, Arrow backend. Use for tabular data in RAM (1–100 GB) when pandas is too slow. Expression API: select, filter, group_by, joins, pivots, window. Lazy mode enables predicate/projection pushdown. Reads CSV, Parquet, JSON, Excel, DBs, cloud. Larger-than-RAM: Dask; GPU: cuDF.
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