Results for “models”

Build content-heavy web applications with a full-featured Python framework that includes ORM, admin interface, authentication, and REST API support.

Test-drive Django applications with pytest, factory_boy, and Django REST Framework, covering models, views, serializers, and API endpoints.

Generate production-ready Dataverse SDK solutions with architecture recommendations, data models, and implementation code for common business use cases.

Converts human-written CLAUDE.md files into a structured-label format that AI models follow more reliably while using fewer tokens.

Guides test-driven development for Django applications using pytest, factory_boy, and Django REST Framework, covering models, views, serializers, and API testing.

Generates structured VGL JSON for Bria FIBO models, giving deterministic control over objects, lighting, camera, composition, and style instead of natural language prompts.

Use when designing, creating, or modifying database schemas, data structures, or data models. This skill provides standardized data modeling practices ensuring consistency, integrity, and maintainability across all data stores.

Run state-of-the-art machine learning models directly in JavaScript/TypeScript across browsers and server-side runtimes using Transformers.js.

Write, review, debug, and test Python FastAPI applications with path operations, dependencies, Pydantic models, lifespan, middleware, background tasks, exception handling, and ASGI tests.

Convert human-written CLAUDE.md files into a structured label format that AI models follow more reliably using fewer tokens.

Predict molecular properties, train graph neural networks, and run drug discovery workflows using DeepChem's featurizers, models, and MoleculeNet benchmarks.

Generate and edit high-quality images using OpenRouter's AI models including FLUX.2 Pro and Gemini 3.1 Flash Image Preview.

Train large language models (7B-70B+) with RLHF using PPO, GRPO, DPO, and other algorithms, accelerated by Ray and vLLM for distributed multi-GPU setups.

Guides users through installing, configuring, and verifying the DAWN voice assistant, covering system dependencies, building, models, configuration, admin account, SSL, and optional features.

Provides living project knowledge for the OpenFoodJournal iOS app, including architecture, data models, service contracts, and conventions, to be consulted before any work on the project.

Write, review, debug, or interpret Python statistical models using statsmodels, including formulas, regression, GLM, time series, robust covariance, diagnostics, prediction intervals, and inference.

Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.

Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.

Provides production-grade Django architecture patterns including project structure, model design, REST API design with DRF, ORM best practices, caching, signals, and middleware.

Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning using 100+ featurizers, including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa.

Provides expert guidance for fine-tuning LLMs with LLaMA-Factory, covering WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, and multimodal support.

Plan and govern product content: audit existing material, define content models, establish voice and tone, and set ownership workflows.

Build applications with Gemini API hosted models, including multimodal content, function calling, and structured outputs, using the latest SDKs and model specifications.

Use mmx to generate text, images, video, speech, and music via the MiniMax AI platform. Use when the user wants to create media content, chat with MiniMax models, perform web search, or manage MiniMax

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

Use this when the team needs to define permissions, roles, membership rules, resource ownership, or action-level authorization separate from authentication choice. Trigger on requests about access models, RBAC, ABAC, tenancy, or protected operations.

Detect and fix code-quality and correctness issues in AEM as a Cloud Service projects locally, without external services or network calls.

Design and create AEM Workflow models on AEM 6.5 LTS, covering step types, transitions, variables, and XML deployment via Package Manager or Maven.

Integrates third-party APIs by discovering available SDKs, getting integration guidance, and looking up models and endpoints via the context-matic MCP server.

Index of Odoo 19 development guides covering actions, controllers, data files, decorators, fields, manifests, migrations, mixins, models, OWL components, performance, reports, security, testing, translation, transactions, and views.

Surveys a codebase as a senior advisor and produces prioritized, self-contained implementation plans for other models or agents to execute, without modifying source code.

Create and configure Vapi voice AI assistants with models, voices, transcribers, tools, hooks, and advanced settings. Use when building voice agents, phone bots, customer support assistants, or any conversational AI that handles phone or web calls.

Guides users in setting product or service prices using minimalist entrepreneur principles, covering cost-based and value-based models, tiered pricing, and financial independence math.

Train AI models to be harmless through self-critique and AI feedback using a set of constitutional principles, without requiring human labels for harmful outputs.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.