ML Ops

Machine learning operations

Showing 1225-1248 of 2110 skills
Aznatkoiny

cpp-reinforcement-learning

by Aznatkoiny

C++ Reinforcement Learning best practices using libtorch (PyTorch C++ frontend) and modern C++17/20. Use when: - Implementing RL algorithms in C++ for performance-critical applications - Building production RL systems with libtorch - Creating replay buffers and experience storage - Optimizing RL training with GPU acceleration - Deploying RL models with ONNX Runtime

Kubernetes 10 8mo ago
deusyu

car-advisor

by deusyu

实时汽车问答与对比分析系统。当用户询问任何买车、选车、汽车参数对比、车型评测、价格分析相关问题时触发此 Skill。 触发场景(只要涉及以下任一情形就必须使用此 Skill): - 车型参数对比:"小米SU7和Model 3哪个好"、"国产车和特斯拉对比" - 配置/价格查询:"Model Y 焕新版座椅加热有吗"、"问界M9多少钱" - 真实车主评价:"XX车口碑怎么样"、"懂车帝评分" - 购车决策辅助:"20-30万预算推荐什么车"、"新能源SUV怎么选" - 车辆功能查询:"这款车支持V2L吗"、"有没有露营模式" - 销量/市场数据:"2024年最畅销新能源车" 即使用户没有明确说"帮我对比"或"查一下",只要话题涉及具体车型的任何属性,都应该主动触发此 Skill 进行实时数据检索,而不是依赖训练数据回答。

Processing 10 8mo ago
TinyAssets

tinyassets-status

by TinyAssets

Show TinyAssets status from the hosted MCP server at tinyassets.io.

ML Ops 1 12d ago
bejranonda

performance-scaling

by bejranonda

Cross-model performance optimization and scaling configurations for autonomous agents

ML Ops 28 12mo ago
CloudAI-X

world-labs-text-prompt

by CloudAI-X

Text-to-world generation best practices, prompt structure, style descriptors

ML Ops 4 9mo ago
HJewkes

buildkite

by HJewkes

Buildkite CI/CD integration. Use when the user needs to check build status, trigger builds, read build logs, debug failures, manage pipelines, or any Buildkite workflow. Triggers include "buildkite", "build", "pipeline", "CI", "deploy", "build log", "build failed".

CI/CD 4 8mo ago
magnusthovsland

segment-anything-model

by magnusthovsland

"SAM: zero-shot image segmentation via points, boxes, masks."

Code Gen 0 4mo ago
mamba-mental

Google ADK Python Skill

by mamba-mental

Remember: ADK treats agent development like traditional software engineering - use version control, write tests, and follow engineering best practices.

Agents 4 9mo ago
Harryoung

expert-routing

by Harryoung

Domain expert routing. When the knowledge base cannot answer user questions, find and notify the corresponding expert based on the question domain. Only available in IM mode. Trigger condition: No results in 6-stage retrieval.

Agents 104 9mo ago
magnusthovsland

weights-and-biases

by magnusthovsland

"W&B: log ML experiments, sweeps, model registry, dashboards."

File Ops 0 4mo ago
magnusthovsland

jupyter-live-kernel

by magnusthovsland

"Iterative Python via live Jupyter kernel (hamelnb)."

API Dev 0 3mo ago
nokonoko1203

codex

by nokonoko1203

"Delegate to Codex CLI for implementation, testing, review, or design consultation. Triggers: codex, ask codex, codex review, review this, second opinion"

Code Review 92 8mo ago
itsmostafa

transformers

by itsmostafa

Loading and using pretrained models with Hugging Face Transformers. Use when working with pretrained models from the Hub, running inference with Pipeline API, fine-tuning models with Trainer, or handling text, vision, audio, and multimodal tasks.

CI/CD 24 9mo ago
oci-ai-architects

Agentic Orchestration for Oracle Cloud

by oci-ai-architects

Claude Code skills for OCI AI Architects. Community-led reference implementations and patterns.

Agents 5 8mo ago
L-yifan

outlines

by L-yifan

Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library

Code Gen 5 7mo ago
L-yifan

dspy

by L-yifan

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

ML Ops 5 7mo ago
L-yifan

sentence-transformers

by L-yifan

Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.

Embeddings 5 7mo ago
DimitriGilbert

openrouter

by DimitriGilbert

Expert OpenRouter API assistant for AI agents. Use when making API calls to OpenRouter's unified API for 400+ AI models. Covers chat completions, streaming, tool calling, structured outputs, web search, embeddings, multimodal inputs, model selection, routing, and error handling.

Processing 5 8mo ago
twofoldtech-dakota

frontend-razor

by twofoldtech-dakota

Apply when working with Razor views, MVC layouts, partial views, and tag helpers

Email 3 9mo ago
raintree-technology

aptos-object-model

by raintree-technology

Expert on Aptos Object Model for composable, transferable assets. Covers ObjectCore, Object<T> wrapper, ConstructorRef, ExtendRef, DeleteRef, TransferRef capabilities, object ownership, named vs generated objects, and composability patterns.

Code Gen 84 9mo ago
raintree-technology

shelby

by raintree-technology

Shelby Protocol expert for decentralized blob storage on Aptos blockchain. Covers erasure coding (Clay Codes), TypeScript SDK, smart contracts, CLI tools, storage providers, and dApp integration. High-performance storage for video streaming, AI training, and large datasets. Triggers on Shelby, Shelby Protocol, decentralized storage, Aptos storage, blob storage, ShelbyNodeClient, erasure coding, Clay Codes.

Processing 84 9mo ago
nahisaho

ai-ml-engineer

by nahisaho

Copilot agent that assists with machine learning model development, training, evaluation, deployment, and MLOps Trigger terms: machine learning, ML, AI, model training, MLOps, model deployment, feature engineering, model evaluation, neural network, deep learning Use when: User requests involve ai ml engineer tasks.

Processing 79 10mo ago
younes-io

tlaplus-workbench

by younes-io

"Write and iteratively refine executable TLA+ specs (.tla) and TLC model configs (.cfg) from natural-language system designs; run TLC model checking; summarize pass/fail and counterexamples with explicit assumptions and bounds. Use when asked to: design/validate a state machine or distributed protocol with TLA+, create/edit .tla or .cfg files, run TLC, or interpret TLC failures/counterexamples."

Processing 21 8mo ago
404kidwiz

ML/AI Skills Conversion Project

by 404kidwiz

Follow the existing patterns to implement these skills.

Processing 75 9mo ago