Explore our collection of Agent Skills to enhance your AI workflow.
Optimizes large-scale model training using DeepSpeed configurations, ZeRO optimization stages, and high-performance I/O management.
Implements advanced PyTorch FSDP2 sharding and distributed checkpointing for efficient large-scale model training.
Scales LLM post-training via reinforcement learning by integrating Megatron-LM training with high-throughput SGLang inference.
Implements, fine-tunes, and deploys high-performance Large Language Models using Lightning AI's LitGPT framework.
Implements Group Relative Policy Optimization (GRPO) for reasoning and task-specific model alignment using the TRL library.
Integrates Pinecone's managed vector database to power high-performance RAG, semantic search, and recommendation systems.
Extracts and validates structured data from LLM responses using Pydantic for reliable, type-safe outputs and automatic retries.
Implements efficient similarity search and clustering for dense vectors at scale using Facebook AI's high-performance library.
Provisions and manages high-performance GPU infrastructure on Lambda Labs for machine learning training and inference workflows.
Manage the complete machine learning lifecycle including experiment tracking, model versioning, and deployment using the MLflow framework.
Moderates LLM inputs and outputs using Meta's specialized LlamaGuard models to ensure safety and policy compliance across six critical categories.
Generates high-quality images from text and performs advanced image-to-image transformations using the HuggingFace Diffusers library.
Optimizes large language models for efficient local inference using GGUF format and llama.cpp quantization techniques.
Streamlines the fine-tuning of 100+ large language models using LLaMA-Factory with support for QLoRA and multimodal architectures.
Implements a minimalist, educational GPT-2 architecture in PyTorch for learning and training transformer models from scratch.
Interprets and manipulates neural network internals across local and remote models using the nnsight library and NDIF execution.
Trains large language models using advanced reinforcement learning algorithms like GRPO and PPO with the production-ready verl framework.
Manages high-performance vector similarity search and scalable storage for production RAG and semantic search systems.
Builds, deploys, and manages continuous AI agents through a visual workflow builder or specialized development toolkit.
Transcribes and translates audio across 99 languages using OpenAI's robust general-purpose speech recognition models.
Manages high-performance vector embeddings and metadata for RAG applications and semantic search using the open-source Chroma database.
Combines multiple fine-tuned AI models into a single high-performance model without requiring additional training or expensive GPU resources.
Analyzes and manipulates transformer model internals using mechanistic interpretability techniques like activation patching and circuit analysis.
Standardizes and accelerates PyTorch model training with built-in support for distributed computing, logging, and engineering best practices.
Deploys and manages high-performance RLHF training pipelines for large-scale language models using Ray and vLLM acceleration.
Renders high-performance geospatial visualizations and interactive maps using WebGL-powered layers.
Transforms Claude into a personalized programming mentor that uses your actual codebase to teach senior-level engineering concepts through spaced repetition and interactive quizzes.
Captures and organizes multi-agent programming design patterns to build a searchable architectural knowledge base.
Implements advanced multi-agent design patterns for building robust LLM applications with the Langroid framework.
Crafts purposeful internal directory documentation that explains organizational logic and architectural context.
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