Claude Skills by VectorSpaceLab

"Routes INT8 calibration, calibration-image preparation, and

"Routes DeepStream-Yolo exporter selection, ONNX conversion, and

"Routes DeepStream-Yolo tasks that run multiple detectors in one

"Use DeepVariant and DeepTrio for genomics variant-calling command

"Plan and interpret DeepVariant VCF stats, runtime-by-region,

"Plan, validate, and adapt standard DeepVariant germline

"Use pangenome-aware DeepVariant with GBZ inputs and

"Understand and adapt DeepVariant make_examples, call_variants,

"Plan DeepVariant labeled-example generation, custom training,

"Plans DeepTrio trio and duo variant-calling workflows with child

"Use DeepXDE for scientific machine learning, PINNs,

"Install and select DeepXDE tensor backends and configure dtype,

"Use DeepXDE operator-learning data classes and networks: DeepONet,

"Assemble DeepXDE forward and inverse PINN problems with geometry,

"Guide DeepXDE model lifecycle, optimizers, callbacks, prediction,

"Use the DeepXiv SDK for citation-aware academic and web research

"Operate the DeepXiv command-line interface safely: choose commands

"Operate DeepXiv's optional OpenAI-compatible LangGraph ReAct Agent

"Use the DeepXiv Reader for hosted arXiv/web agentic research,

"Use denoising-diffusion-pytorch for PyTorch DDPM/DDIM image

"Advanced denoising-diffusion-pytorch variants: Karras UNets,

"Use denoising-diffusion-pytorch conditioning and guidance APIs:

"Operate 2D image DDPM/DDIM workflows with

"Use denoising-diffusion-pytorch for 1D sequence diffusion with

"Guide Det3D PyTorch 3D object-detection workflows across

"Safely inspect and validate Det3D Python configurations,

"Route Det3D dataset layout, metadata conversion, annotation,

"Route Det3D installation, import, CUDA extension, PyTorch ABI,

"Route Det3D training, inference, evaluation, checkpoint, resume,

"Route Det3D LiDAR, BEV, KITTI, prediction, training-log, FLOPs,

"Use Detectron2 for object detection, segmentation, configuration,

"Choose, load, inspect, modify, and validate Detectron2 Yacs,

"Register and validate Detectron2 datasets, metadata, COCO helpers,

"Export, inspect, and benchmark Detectron2 models with TorchScript,

"Extend Detectron2 with registries, configurable model components,

"Run Detectron2 inference, inspect model outputs, and visualize

"Train, evaluate, checkpoint, and troubleshoot Detectron2 models

"Load, generate, compile, rasterize, evaluate, train, and serve

"Work with DeTikZify dataset helpers, local dataset fallbacks,

"Evaluate DeTikZify outputs with metric wrappers, score generated

"Load DeTikZify models and adapters, build inference pipelines,

"Prepare and reason about DeTikZify training, pretraining,

"Launch and troubleshoot DeTikZify's Gradio web UI, choose models

"Use detrex for detection-transformer configs, training/evaluation,

"Route detrex model zoo selection, pretrained backbones, and safe

"Inspect and use detrex Python APIs for layers, losses, matchers,

"Routes detrex demo, analysis, visualization, benchmark planning,

"Plan detrex LazyConfig training, evaluation, dataset, launcher,

"Use Dexbotic to prepare DexData, train and serve

"Prepare, validate, register, and troubleshoot Dexbotic DexData