搜索「3D Models」的结果

io.github.discourse/discourse/discourse-warpdrive-models

Use when creating a new WarpDrive-backed frontend model, or when reading, using, or changing a model already converted to WarpDrive (anything under frontend/discourse/app/data or extending RestCompatModel/WarpRestModel)

io.github.K-Dense-AI/scientific-agent-skills/statsmodels

Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided statistical test selection with APA reporting use statistical-analysis.

io.github.NVIDIA/skills/vss-deploy-detection-tracking-3d

Deploy and operate the RTVI-CV-3D microservice as MV3DT (`MODE=mv3dt`): per-camera DeepStream perception plus BEV Fusion over calibrated cameras. Supports the bundled sample dataset, custom video files, and RTSP streams, and chains to `vss-generate-video-calibration` when calibration is missing. Use `vss-deploy-profile` for the full warehouse blueprint and `vss-deploy-detection-tracking-2d` for single-camera 2D detection.

io.github.aiskillstore/marketplace/backend-models

Define database models and ORM entities with proper naming, relationships, validation, and data integrity constraints. Use this skill when creating or modifying model classes, database table definitions, model relationships (one-to-many, many-to-many), data validation rules, database constraints, or model methods. Apply when working with ORM model files, ActiveRecord, SQLAlchemy, Sequelize, Prisma schemas, or any database model definitions that map objects to database tables and enforce data structure and relationships.

io.github.aiskillstore/marketplace/backend-models

Define and configure database models with proper naming, relationships, timestamps, data types, constraints, and validation. Use this skill when creating or editing model files in app/Models/, Eloquent model classes, model relationships (hasMany, belongsTo, etc.), database table structures, model attributes and casts, model factories, or seeders. Use when working on model validation logic, database constraints, foreign key relationships, indexes, scopes, accessors, mutators, or any ORM-related model configuration.

io.github.NVIDIA-AI-Blueprints/video-search-and-summarization/vss-deploy-detection-tracking-3d

Deploy and operate the RTVI-CV-3D microservice as MV3DT (`MODE=mv3dt`): per-camera DeepStream perception plus BEV Fusion over calibrated cameras. Supports the bundled sample dataset, custom video files, and RTSP streams, and chains to `vss-generate-video-calibration` when calibration is missing. Use `vss-deploy-profile` for the full warehouse blueprint and `vss-deploy-detection-tracking-2d` for single-camera 2D detection.

io.github.jeremylongshore/claude-code-plugins-plus-skills/deploying-machine-learning-models

Deploy this skill enables AI assistant to deploy machine learning models to production environments. it automates the deployment workflow, implements best practices for serving models, optimizes performance, and handles potential errors. use this skill when th... Use when deploying or managing infrastructure. Trigger with phrases like 'deploy', 'infrastructure', or 'CI/CD'.

io.github.tedivm/robs_awesome_python_template/sqlalchemy-models

Create or modify SQLAlchemy models, queries, and Alembic migrations. Use when: defining new database tables, writing queries, creating migrations, checking model conventions, or understanding the database layer.

io.github.getsentry/sentry/django-models

Design Django ORM models for Sentry following architectural conventions for silos, replication, relocation, and foreign keys. Use when adding a new Django model, designing a model for a feature, deciding where data should live, picking a foreign key type, or refactoring an existing model's silo placement. Trigger on "add a Django model", "create a model", "design a model for X", "new database table", "store this data in the DB", "I need to track Y", "model for [feature]". Not for Pydantic models, dataclasses, ML models, or Protobuf — this is specifically for Django ORM models in the Sentry codebase.

io.github.Microck/ordinary-claude-skills/backend-models-standards

Define database models with clear naming, appropriate data types, constraints, relationships, and validation at multiple layers. Use this skill when creating or modifying database model files, ORM classes, schema definitions, or data model relationships. Apply when working with model files (e.g., models.py, models/, ActiveRecord classes, Prisma schema, Sequelize models), defining table structures, setting up foreign keys and relationships, configuring cascade behaviors, implementing model validations, adding timestamps, or working with database constraints (NOT NULL, UNIQUE, foreign keys). Use for any task involving data integrity enforcement, relationship definitions, or model-level data validation.

io.github.modelscope/AgentJet/docker-install-agentjet-swarm-server

Install and run the AgentJet Swarm Server in a Docker container with NVIDIA GPU support. Use when the user wants to deploy a swarm server on a GPU machine via Docker, including GPU driver setup, Docker mirror configuration, model weight mounting, and server startup.

io.github.modelscope/ms-agent/pdf

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

io.github.K-Dense-AI/scientific-agent-skills/datamol

Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.

io.github.nextlevelbuilder/ui-ux-pro-max-skill/banner-design

Design banners for social media, ads, website heroes, creative assets, and print. Multiple art direction options with optional generated or supplied visuals. Actions: design, create, generate banner. Platforms: Facebook, Twitter/X, LinkedIn, YouTube, Instagram, Google Display, website hero, print. Styles: minimalist, gradient, bold typography, photo-based, illustrated, geometric, retro, glassmorphism, 3D, neon, duotone, editorial, collage.

io.github.heygen-com/hyperframes/hyperframes-keyframes

Use when a HyperFrames composition needs a punch-in, punch-out, zoom, reframe, Ken Burns treatment, camera move, visual match/whip handoff, or other seek-safe 2D/3D keyframes; also for GSAP, CSS keyframes, Anime.js, WAAPI, FLIP, paths, masks, SVG morph/draw, text trails, 3D depth, or `hyperframes keyframes` diagnostics. Don't use for broad scene strategy, brand design, media sourcing, captions, or general video planning.

io.github.nexu-io/open-design/threejs

Three.js skills for creating 3D elements and interactive experiences in the browser — scenes, materials, controls, and post-processing.

io.github.nexu-io/open-design/open-design-homepage

A pixel-faithful, self-contained mirror of the live open-design.ai homepage — an interactive React Three Fiber / Next.js hero with a real-time 3D wordmark, sticker collage, variable fonts, and scroll-driven motion. First-party showcase of the visual ceiling for interactive web marketing surfaces.

io.github.nexu-io/open-design/webgl-depth-gallery

A scroll-reactive 3D image gallery in Three.js: Z-stacked images crossfade over per-image mood backgrounds with velocity breath, a glowing cursor trail and an editorial CMYK/RGB/HEX/PMS color card.

io.github.affaan-m/ECC/remotion-video-creation

Best practices for Remotion - Video creation in React. 29 domain-specific rules covering 3D, animations, audio, captions, charts, transitions, and more. Use when building video in React with Remotion — animations, audio, captions, charts, or transitions.

io.github.microsoft/ai-agents-for-beginners/local-ai-agents

Bumuo ng mga local-first AI agents na tumatakbo nang buong-buo sa isang developer workstation gamit ang Microsoft Foundry Local at Qwen function-calling models. Saklaw nito ang Small Language Models (SLMs), ang OpenAI-compatible na lokal na endpoint, sandboxed local tools, lokal na RAG gamit ang Chroma, lokal na MCP servers, hybrid cloud/local routing, at ang privacy/cost/offline trade-offs. Batay sa Lesson 17 ng AI Agents for Beginners. GAMITIN PARA SA: pagpapatakbo ng agent nang lokal, offline agent, on-device agent, Foundry Local, Qwen function calling, local tool calling, lokal na RAG, Chroma vector database, lokal na MCP server, privacy-preserving agent, hybrid local at cloud agent, small language model agent, engineering assistant sa aking makina. HUWAG GAMITIN PARA SA: pag-deploy ng mga agents sa cloud nang malakihan (gamitin ang deploying-scalable-agents / Lesson 16), paggawa ng iyong unang agent concept (Lesson 01), Foundry (cloud) hosted agents, GPU cluster / server-side inference provisioning.

io.github.microsoft/ai-agents-for-beginners/local-ai-agents

Build local-first AI agents wey dey run fully for developer workstation wit Microsoft Foundry Local and Qwen function-calling models. E cover Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG wit Chroma, local MCP servers, hybrid cloud/local routing, and di privacy/cost/offline trade-offs. E based on Lesson 17 of AI Agents for Beginners. USE FOR: run agent locally, offline agent, on-device agent, Foundry Local, Qwen function calling, local tool calling, local RAG, Chroma vector database, local MCP server, privacy-preserving agent, hybrid local and cloud agent, small language model agent, engineering assistant for my machine. DO NOT USE FOR: deploying agents to di cloud at scale (use deploying-scalable-agents / Lesson 16), building your first agent concept (Lesson 01), Foundry (cloud) hosted agents, GPU cluster / server-side inference provisioning.

io.github.microsoft/ai-agents-for-beginners/local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the privacy/cost/offline trade-offs. Based on Lesson 17 of AI Agents for Beginners. USE FOR: run an agent locally, offline agent, on-device agent, Foundry Local, Qwen function calling, local tool calling, local RAG, Chroma vector database, local MCP server, privacy-preserving agent, hybrid local and cloud agent, small language model agent, engineering assistant on my machine. DO NOT USE FOR: deploying agents to the cloud at scale (use deploying-scalable-agents / Lesson 16), building your first agent concept (Lesson 01), Foundry (cloud) hosted agents, GPU cluster / server-side inference provisioning.

io.github.microsoft/ai-agents-for-beginners/local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the privacy/cost/offline trade-offs. Based on Lesson 17 of AI Agents for Beginners. USE FOR: run an agent locally, offline agent, on-device agent, Foundry Local, Qwen function calling, local tool calling, local RAG, Chroma vector database, local MCP server, privacy-preserving agent, hybrid local and cloud agent, small language model agent, engineering assistant on my machine. DO NOT USE FOR: deploying agents to the cloud at scale (use deploying-scalable-agents / Lesson 16), building your first agent concept (Lesson 01), Foundry (cloud) hosted agents, GPU cluster / server-side inference provisioning.

io.github.camunda/camunda/frontend-integration-test

Use when writing, modifying, or debugging Playwright tests in the orchestration cluster webapp — integration tests, visual regression, or accessibility tests; MSW mocking, Page Object Models, or axe-core. Test directory: webapp/client/apps/orchestration-cluster-webapp/test/.