ML Ops
Machine learning operations
clip
by ovachiever
OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.
huggingface-accelerate
by ovachiever
Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.
quantizing-models-bitsandbytes
by ovachiever
Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
audio-to-text
by lucas-acc
Transcribe audio files to text with automatic language detection (supports Chinese and English)
consulting-frameworks
by Aznatkoiny
Core consulting thinking frameworks and methodologies for structuring business problems, communicating findings, analyzing strategy, building financial models, and designing operations. Use when any agent or command needs to apply MECE decomposition, pyramid principle, hypothesis-driven analysis, issue trees, SCR communication, Porter's Five Forces, TAM/SAM/SOM market sizing, value chain analysis, NPV/IRR decision criteria, build/buy/partner evaluation, RACI matrices, or any standard consulting framework. This skill provides procedural guidance — not just framework names, but how to apply them correctly.
claude
by G1Joshi
Anthropic Claude AI models for analysis and coding. Use for AI assistants.
ray
by G1Joshi
Ray distributed computing framework. Use for scaling ML.
deepseek
by G1Joshi
DeepSeek AI models for coding. Use for code AI.
catboost
by G1Joshi
CatBoost gradient boosting with categoricals. Use for tabular ML.
stable-diffusion
by G1Joshi
Stable Diffusion image generation models. Use for image AI.
weights-biases
by G1Joshi
Weights & Biases ML experiment tracking. Use for ML monitoring.
mistral
by G1Joshi
Mistral AI efficient open models. Use for efficient AI.
jax
by G1Joshi
JAX high-performance numerical computing. Use for ML research.
role-architect:cost-modeling
by rnavarych
Cost modeling expertise including infrastructure cost estimation, TCO calculation, build vs buy analysis, pricing model comparison, ROI projection, cost growth modeling, and breakeven analysis.
model-thinking
by kcchien
Mental models toolkit for clearer thinking, better decisions, and problem-solving. Use when users face complex problems, need decision support, want to analyze situations from multiple angles, organize information, understand systems, predict outcomes, or learn about specific mental models. Triggers include phrases like "help me think through", "analyze this problem", "what models apply here", "how should I decide", "evaluate options", or direct model references (e.g., "use second-order thinking", "apply inversion"). 中文觸發：「思維模型」、「幫我分析」、「決策分析」、「多角度思考」、「怎麼判斷」、「幫我想清楚」、「系統思考」、「風險評估」。
role-architect:system-design
by rnavarych
System design expertise including requirements analysis, C4 model diagrams, sequence diagrams, data flow diagrams, trade-off documentation, capacity estimation, distributed systems theory, load balancing algorithms, caching architectures, message-driven and stream processing architectures, data pipeline design, search architecture, and system design patterns for common internet-scale systems (URL shorteners, chat, news feed, rate limiters).
skills
by atxinsky
Execute plan in batches with review checkpoints
skills
by atxinsky
Create detailed implementation plan with bite-sized tasks
affiliate-onboarding
by dmend3z
This skill guides users in setting up a robust affiliate onboarding system. It covers welcome sequences, swipe file creation, training curriculum, compliance guidelines, resource library setup, first promotion guidance, and communication templates to transform new affiliates into high-performing partners.
debug:scikit-learn
by SnakeO
Debug Scikit-learn issues systematically. Use when encountering model errors like NotFittedError, shape mismatches between train and test data, NaN/infinity value errors, pipeline configuration issues, convergence warnings from optimizers, cross-validation failures due to class imbalance, data leakage causing suspiciously high scores, or preprocessing errors with ColumnTransformer and feature alignment.
pydantic-ai-agents
by Fuenfgeld
"Build and debug Pydantic AI agents using best practices for dependencies, dynamic system prompts, tools, and structured output validation. Use when the user wants to: (1) Create a new Pydantic AI agent, (2) Debug or fix an existing agent, (3) Add features like tools, validators, or dynamic prompts, (4) Integrate OpenRouter for multi-model access, (5) Add Logfire for debugging/observability, (6) Structure agent architecture with dependency injection."
affiliate-motivation-and-training
by dmend3z
This skill equips the agent to motivate and train affiliate partners effectively. It should be used for tasks like creating weekly updates, sharing success stories, developing training modules, writing personal outreach scripts, planning reactivation campaigns, and designing performance coaching and incentive programs.
ai-ml-senior-engineer
by mOdrA40
Elite AI/ML Senior Engineer with 20+ years experience. Transforms Claude into a world-class AI researcher and engineer capable of building production-grade ML systems, LLMs, transformers, and computer vision solutions. Use when: (1) Building ML/DL models from scratch or fine-tuning, (2) Designing neural network architectures, (3) Implementing LLMs, transformers, attention mechanisms, (4) Computer vision tasks (object detection, segmentation, GANs), (5) NLP tasks (NER, sentiment, embeddings), (6) MLOps and production deployment, (7) Data preprocessing and feature engineering, (8) Model optimization and debugging, (9) Clean code review for ML projects, (10) Choosing optimal libraries and frameworks. Triggers: "ML", "AI", "deep learning", "neural network", "transformer", "LLM", "computer vision", "NLP", "TensorFlow", "PyTorch", "sklearn", "train model", "fine-tune", "embedding", "CNN", "RNN", "LSTM", "attention", "GPT", "BERT", "diffusion", "GAN", "object detection", "segmentation".
django-model-helper
by Dexploarer
Generates Django models with proper field types, relationships, and migrations. Use when creating Django models or database schemas.