VectorSpaceLab

Routes DocsGPT deployment, source ingestion, retrieval, agent workflows, tools, integrations, and native or OpenAI-compatible API operations.

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Routes EasyCV training, evaluation, prediction, export, and data workflows.

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Guides Earth2Studio weather and climate inference workflows, data access, model and component selection, output/checkpoint handling, extension, and optional REST serving with backend-aware validation.

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Use DreamCraft3D for image-conditioned 3D generation, staged optimization, texture boosting, export, and CUDA troubleshooting.

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Route DataFlow workflows for pipelines, text and document processing, serving, evaluation, and Ray acceleration.

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Use this repo skill for Dask, the Python parallel computing library, when working with lazy task graphs, schedulers, Dask Array, Dask DataFrame, Dask Bag/bytes IO, configuration, diagnostics, CLI usage, or contributor validation.

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Use when building, debugging, testing, or maintaining Plotly Dash applications, callbacks, server backends, component packages, renderer internals, and Dash repository workflows.

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Routes Darkflow object-detection, training, and export workflows for the legacy YOLO package.

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Use the DALLE2-pytorch package for DALL-E 2 style text-to-image model APIs, diffusion prior/decoder training, WebDataset data layouts, and tracker/checkpoint workflows.

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Operate lucidrains DALLE-pytorch for DALL-E style VAE training, transformer training, generation, CLIP ranking, and backend troubleshooting.

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Router for CVNets training, evaluation, registry, data, and export workflows.

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Operate CVAT for computer-vision annotation, dataset workflows, SDK/CLI automation, auto-annotation, and self-hosted deployment.

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Route Custom Diffusion workflows for concept data prep, diffusers training and SDXL, sample generation, delta tools, and CustomConcept101 evaluation.

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Guides CUDA-accelerated cuRobo v2 robotics workflows for robot models, differentiable kinematics, collision-aware IK and motion planning, trajectory optimization, MPC, perception mapping, and motion retargeting.

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Use DeepFace for face recognition, verification, embeddings, face detection, demographic analysis, datastore search, API serving, model selection, and troubleshooting.

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Route D-FINE object-detection setup, training, architecture inspection, inference, export, and troubleshooting workflows.

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Data-Juicer repo router for local recipes, Ray recovery, and service/MCP workflows.

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Use this skill when working with Hugging Face Datasets: loading local or Hub datasets, defining Features schemas, processing/streaming datasets, converting formats, sharing to the Hub, managing cache/offline behavior, or using datasets-cli.

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Guide Det3D PyTorch 3D object-detection workflows across configuration, KITTI/nuScenes/Lyft data preparation, GPU training and evaluation, custom CUDA operations, and visualization.

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Route DeepSearcher workflows for provider setup, data ingestion, RAG querying, CLI and service operation, and evaluation.

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cuML operating skill for GPU-accelerated classical ML, cuml.accel, Dask multi-GPU workflows, data utilities, and native source-build guidance.

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Use the DataSciencePython tutorial/example collection through modern self-contained helpers for Python data-science resources, statsmodels logistic regression, scikit-learn Kaggle-style tabular classifiers, and Twitter JSONL extraction.

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Use denoising-diffusion-pytorch for PyTorch DDPM/DDIM image diffusion, 1D sequence diffusion, conditioning and guidance, and advanced diffusion variants.

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Use when working with Dagster OSS: assets, jobs, Definitions, config/resources, schedules/sensors, automation, CLI/local development, deployment operations, GraphQL/webserver, Pipes external processes, components/projects, or editing the Dagster repository itself.

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