Route DeepLabCut markerless pose-estimation workflows, project setup, PyTorch training/inference, maDLC tracking, Model Zoo, post-processing, 3D, and export tasks.
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Route DeblurGAN users to data preparation, training, and single-image inference workflows.
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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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Use DeepDanbooru for anime-style image tag estimation, project and Danbooru-style dataset preparation, TensorFlow training, image evaluation, TFLite conversion, and experimental Grad-CAM workflows.
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Use deep-daze for CLIP-guided Siren image generation through the imagine CLI and Python APIs, with runtime inspection and troubleshooting.
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Route DeepFilterNet speech enhancement, Python API/CLI, training data, model export/evaluation, and Rust/LADSPA realtime workflows.
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Training, inference, and deployment workflows for DAMO-YOLO object detection.
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Guide DeepMedic 0.8.4 workflows for multi-modal 3D NIFTI medical-image segmentation, including data preparation, model configuration, training, checkpoint continuation, inference, and CPU/CUDA troubleshooting.
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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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Use DeepFace for face recognition, verification, embeddings, face detection, demographic analysis, datastore search, API serving, model selection, and troubleshooting.
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Data-Juicer repo router for local recipes, Ray recovery, and service/MCP workflows.
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Route D-FINE object-detection setup, training, architecture inspection, inference, export, and troubleshooting workflows.
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Route DeepSearcher workflows for provider setup, data ingestion, RAG querying, CLI and service operation, and evaluation.
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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 the DeepXiv SDK for citation-aware academic and web research through its Python Reader, deepxiv CLI, progressive paper APIs, optional local LangGraph agent, PMC, bioRxiv/medRxiv, and trending workflows.
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Use DeepXDE for scientific machine learning, PINNs, DeepONet/operator learning, backend selection, training, and troubleshooting.
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Use DeepVariant and DeepTrio for genomics variant-calling command planning, input validation, pipeline-stage troubleshooting, custom training, and report analysis.
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Use DeepSpeed for distributed training, inference acceleration, ZeRO configuration, parallelism/MoE design, profiling, autotuning, and operational diagnostics.
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Route DeePMD-kit package workflows for installation, data/config preparation, training, inference/model operations, integrations, and repository development.
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Route DeepKE knowledge extraction workflows across supervised extraction, data prep, triples, LLMs, and MCP tools.
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Use deepjazz for legacy MIDI jazz generation with music21 preprocessing, abstract grammar tokens, Keras/Theano LSTM training, safe diagnostics, and modernization guidance.
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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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Use this DeepCTR repo skill for CTR/recommender feature columns, Keras models, sequence/session models, multitask models, and legacy TensorFlow Estimator workflows.
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Use DeepChem for molecular machine learning, data loading, featurization, model training, MoleculeNet, docking, and optional backend troubleshooting.
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