300 skills (repositories by VectorSpaceLab) · sorted by popularity
Operate FastReID setup, configuration, datasets, model/inference APIs, training/evaluation workflows, deployment/export paths, and extension projects for person and vehicle re-identification.
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Routes FCOS object-detection repo tasks for inference demos, config/data setup, training/evaluation, ONNX export, and legacy PyTorch internals.
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Use davidsandberg/facenet for TensorFlow 1.x face recognition workflows: MTCNN alignment, embeddings, classification, LFW evaluation, training, and model export.
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Guides Researchers through Faiss installation, dense and binary similarity search, index training and composition, persistence and evaluation, and explicitly gated CPU/GPU interoperability workflows.
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Guides FastVideo video, image, and audio generation, config-first inference, serving, training, distillation, evaluation, and performance workflows.
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Operate FATE 2.2.0 federated-learning deployments, FateFlow Pipeline workflows, local launchers, and component CLI/runtime inspection.
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Use this skill for EverOS local-first Markdown memory service setup, HTTP memory and knowledge APIs, cascade/OME operations, and observability integration.
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Use face_recognition to detect faces, extract landmarks and encodings, compare identities, run the face_recognition and face_detection CLIs, and troubleshoot dlib/model installation.
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Use Fairlearn to assess group fairness, compute disparity metrics, visualize subgroup performance, and mitigate unfairness with preprocessing, reductions, postprocessing, or adversarial learning.
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Use the GeoParquet specification and bundled inspection helpers to author, validate, distribute, or safely review geospatial Parquet data, including GeoParquet 2.0 vector metadata, external writer choices, and the alpha Parquet Raster proposal.
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Guides TensorFlow Fast Style Transfer training, image stylization, and video stylization workflows from checkpoints, VGG/COCO assets, and script-oriented CLIs.
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Use the faster-whisper package for CTranslate2-backed Whisper transcription, model selection, CPU/CUDA setup, audio utilities, VAD, timestamps, and conversion guidance.
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Route fastdup workflows for visual dataset curation, annotation-driven analysis, embeddings and search, and video or exchange plumbing.
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Routes face-alignment installation, import checks, landmark-detection workflows, and detector-backend selection.
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Use for Feast feature store tasks: feature repositories, definitions, CLI, retrieval, materialization, serving, RAG/vector search, integrations, and Feast contributor workflows.
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Route GenAI Processors tasks to the right workflow guide.
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Routes evo trajectory-evaluation workflows for APE/RPE, trajectory I/O, result analysis, configuration, and programmatic usage.
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Use ExecuTorch to export PyTorch models to edge runtime artifacts, build host/device runtimes, choose delegates, profile/debug execution, and operate specialized Qualcomm, Cortex-M, LLM, and binary-size workflows.
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Create, polish, and troubleshoot figures4papers-style publication-ready matplotlib figures, including grouped bars, trends, radar charts, heatmaps, concept diagrams, manifolds, and high-DPI/vector export workflows.
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Operate Flash Linear Attention package workflows: setup, kernels, layers/models, KDA/context parallel, and benchmarking.
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Use FlagEmbedding for embedding, reranking, retrieval evaluation, and fine-tuning workflows.
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Use Flair for NLP annotation, embeddings, text/sequence model prediction, corpus loading, training/fine-tuning, HunFlair biomedical NER/linking, and production troubleshooting.
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Use fastMRI for MRI reconstruction data loading, MRI operators, reconstruction models, Lightning training, evaluation, and submission preparation.
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Build, inspect, and reuse Featuretools automated feature engineering workflows for EntitySets, DFS, feature matrices, primitive authoring, feature inspection, and selection.
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