Routes agents working with Axolotl config-driven LLM fine-tuning, datasets, SFT, preference tuning, GRPO/EBFT, model adapters, distributed training, CLI operations, and troubleshooting.
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Route BayesianOptimization package tasks for black-box Bayesian optimization, HPO, acquisition functions, constraints, typed domains, domain reduction, and checkout maintenance.
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Use bitsandbytes for k-bit PyTorch quantization, Hugging Face quantized model loading, 8-bit and paged optimizers, direct quantized layers/functions, and backend installation diagnostics.
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Guides Attention-Gated Networks PyTorch medical imaging workflows for ultrasound classification, attention-gated U-Net segmentation, data layout, CUDA setup, and visualization helpers.
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Use audio-diffusion-pytorch for PyTorch waveform diffusion generators, text-conditioned audio generation, inpainting, upsampling, vocoding, and diffusion autoencoding.
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Use Augmentor for Pillow-based image augmentation pipelines, operation selection, mask-safe augmentation, array/generator workflows, and package-specific troubleshooting.
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Operate the Deep Researcher Agent repository for autonomous deep-learning experiments, execution backends, provider/tool dispatch, GPU resources, durable progress, and research-support integrations.
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Routes automl_gs tabular AutoML searches and the generated runtime artifacts that those searches produce.
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Route BERTopic topic modeling, embedding, vectorizer, labeling, visualization, and serialization workflows.
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Guides CUDA-based BigGAN-PyTorch training, checkpoint sampling, dataset preparation, metric preparation, model customization, and optional TensorFlow Hub weight conversion.
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Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.
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Operate the Agriculture_KnowledgeGraph agricultural Neo4j graph, Django demo, entity labeling, crawler, and relation-extraction workflows.
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Use Argilla 2.x for human-feedback dataset annotation, Python SDK dataset workflows, server deployment/operations, webhooks, and legacy v1/Rubrix migration.
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Use AReaL for large-scale asynchronous LLM reinforcement learning, agentic RL, distributed post-training, inference/agent services, backend planning, and customization workflows.
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Use ArcGIS API for Python for GIS administration, spatial dataframes, feature/raster analysis, mapping, location services, geospatial deep learning, app automation, and Knowledge Graph workflows.
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Use NASA's apod-api Flask service and standalone APOD parser for date, count, range, media, deployment, Docker, and troubleshooting workflows.
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Guides Any4LeRobot dataset conversions, LeRobot-to-RLDS export, and LeRobot v1.6-v3.0 format migrations with schema validation, version-aware environments, and safe publication boundaries.
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Routes AnyDoor zero-shot object-level image customization workflows.
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Routes Agent Starter Pack tasks to the right workflow for creating, maintaining, and deploying generated agent projects.
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Use AiZynthFinder for retrosynthetic planning, configuration, route analysis, custom extensions, and focused development workflows.
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Operate AnyLabeling desktop annotation, auto-labeling model, dataset export, install, packaging, and release workflows for the PyQt6/ONNX image-labeling package.
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Route Apache Airflow repo tasks across Dag authoring, operations, providers, deployment, and contribution workflows.
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Use ANTsPy/antspyx for medical image IO, ANTsImage metadata, image operations, registration, segmentation, visualization, and learning helper workflows.
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Routes AdelaiDet users through legacy-compatible setup, model config selection, training/evaluation, demos, text spotting, dataset preparation, and export/conversion workflows.
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