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Route GeoAI geospatial data, inference, training, foundation-model, and integration workflows.

中文简介正在准备中。当前显示原文说明。

Use geemap for Google Earth Engine interactive mapping, geospatial conversion, visualization, timelapse, and ML helper 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.

中文简介正在准备中。当前显示原文说明。

Route DRL-Pytorch reinforcement-learning workflows for standalone PyTorch Q-learning, DQN-family, PPO, DDPG, TD3, SAC, Atari DQN, and Actor-Sharer-Learner scripts.

中文简介正在准备中。当前显示原文说明。

Route DGL graph learning tasks across graph APIs, datasets, message passing, GraphBolt, distributed tools, and DGL-Go workflows.

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Use DreamerV2 2.2.0 for TensorFlow world-model reinforcement-learning training, custom Gym integration, typed experiment configuration, replay/checkpoint management, and JSONL/TensorBoard evaluation.

中文简介正在准备中。当前显示原文说明。

Use DreamerV3 for world-model reinforcement learning training, embodied environment dataflow, JAX model internals, result operations, and troubleshooting.

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Use DPM-Solver and DPM-Solver++ single-file samplers for diffusion ODE sampling, PyTorch/JAX integration, ScoreSDE/DDPM examples, and Stable Diffusion acceleration.

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Routes Distil-Whisper inference, PyTorch distillation training, and Flax reproduction workflows.

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Guide ROS/Gazebo Velodyne mobile-robot navigation with the DRL-robot-navigation TD3 implementation, including simulator setup, environment contracts, bounded training, checkpoints, and policy evaluation.

中文简介正在准备中。当前显示原文说明。

Use and troubleshoot the Dream Textures Blender add-on for Stable Diffusion image generation, texture projection, render passes, model setup, and backend APIs.

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Routes DreamOmni2 image generation, image editing, and Gradio demo workflows.

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Use Dipy for diffusion MRI IO, preprocessing, reconstruction, tractography, registration, visualization-aware workflows, and command-line operations.

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Use Docling to convert, parse, configure, extract, chunk, serve, and maintain document-processing workflows across Python APIs, CLI commands, optional pipelines, and repository edits.

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Use DeepMind dm-haiku as a JAX neural-network library for transforms, modules, state/RNG, layers, advanced JAX interop, and optional Flax interop.

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

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Guide Django REST Framework and GeoDjango projects through django-rest-framework-gis installation, GeoJSON serialization, spatial filtering, pagination, OpenAPI schema generation, and backend troubleshooting.

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Use DeepMind dm_control for MuJoCo simulation, Control Suite environments, PyMJCF models, Composer tasks, rendering, and high-level locomotion/manipulation workflows.

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Use python-doctr (docTR) for OCR/KIE inference, document IO/export, model customization, datasets/training/evaluation, CLI helpers, deployment, and troubleshooting.

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Use Diffusion Policy for robot imitation-learning configs, zarr replay data, policy/model interfaces, training/evaluation workflows, and safety-gated real robot operations.

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Routes DINO DETR object-detection setup, COCO data validation, CUDA deformable-attention preparation, training, evaluation, inference, visualization, and bounded benchmarking tasks.

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Use Donut for OCR-free document understanding, checkpoint inference, fine-tuning, evaluation, and SynthDoG synthetic document generation.

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Use Diffusion Planner for nuPlan autonomous-driving trajectory generation: prepare model-ready data, train or resume the diffusion model, configure closed-loop planning, and add differentiable collision or classifier guidance.

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Use this repo skill for DiscoArt image generation, configuration/prompt scheduling, CLI, Jina serving, Docker runtime planning, and troubleshooting.

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